• How can geospatial technologies be harnessed to geolocate tweets that pose a political security risk?

ISIS- Islamic State of Iraq and Syria
MENA- Middle East and North Africa
GeoSN- Geo-social network






Recently, the use of Twitter data has become important for a wide range of real-time applications, including real-time event detection, topic detection or disaster and emergency management. These applications require to know the precise location of the tweets for their analysis. However, approximately 1% of the tweets are finely-grained geotagged, which remains insufficient for such applications. To overcome this limitation, predicting the location of non-geotagged tweets, while challenging, can increase the sample of geotagged data to support the applications mentioned above. Nevertheless, existing approaches on tweet geolocalisation are mostly focusing on the geolocation of tweets at a coarse-grained level of granularity (i.e., city or country level). Thus, geolocalising tweets at a fine-grained level (i.e., street or building level) has arisen as a newly open research problem. In this thesis, we investigate the problem of inferring the geolocation of non-geotagged tweets at a fine-grained level of granularity (i.e., at most 1 km error distance). In particular, we aim to predict the geolocation where a given tweet was generated using its text as a source of evidence.
This thesis states that the geolocalisation of non-geotagged tweets at a fine-grained level can be achieved by exploiting the characteristics of the 1\% of already available individual finely-grained geotagged tweets provided by the Twitter stream. We evaluate the state-of-the-art, derive insights on their issues and propose an evolution of techniques to achieve the geolocalisation of tweets at a fine-grained level.
First, we explore the existing approaches in the literature for tweet geolocalisation and derive insights on the problems they exhibit when adapted to work at a fine-grained level. To overcome these problems, we propose a new approach that ranks individual geotagged tweets based on their content similarity to a given non-geotagged. Our experimental results show significant improvements over previous approaches.
Next, we explore the predictability of the location of a tweet at a fine-grained level in order to reduce the average error distance of the predictions. We postulate that to obtain a fine-grained prediction a correlation between similarity and geographical distance should exist, and define the boundaries were fine-grained predictions can be achieved. To do that, we incorporate a majority voting algorithm to the ranking approach that assesses if such correlation exists by exploiting the geographical evidence encoded within the Top-N most similar geotagged tweets in the ranking. We report experimental results and demonstrate that by considering this geographical evidence, we can reduce the average error distance, but with a cost in coverage (the number of tweets for which our approach can find a fine-grained geolocation).
Furthermore, we investigate whether the quality of the ranking of the Top-N geotagged tweets affects the effectiveness of fine-grained geolocalisation, and propose a new approach to improve the ranking. To this end, we adopt a learning to rank approach that re-ranks geotagged tweets based on their geographical proximity to a given non-geotagged tweet. We test different learning to rank algorithms and propose multiple features to model fine-grained geolocalisation. Moreover, we investigate the best performing combination of features for fine-grained geolocalisation.
This thesis also demonstrates the applicability and generalisation of our fine-grained geolocalisation approaches in a practical scenario related to a traffic incident detection task. We show the effectiveness of using new geolocalised incident-related tweets in detecting the geolocation of real incidents reports, and demonstrate that we can improve the overall performance of the traffic incident detection task by enhancing the already available geotagged tweets with new tweets that were geolocalised using our approach.
The key contribution of this thesis is the development of effective approaches for geolocalising tweets at a fine-grained level. The thesis provides insights on the main challenges for achieving the fine-grained geolocalisation derived from exhaustive experiments over a ground truth of geotagged tweets gathered from two different cities. Additionally, we demonstrate its effectiveness in a traffic incident detection task by geolocalising new incident-related tweets using our fine-grained geolocalisation approaches.

Recently, the use of Twitter data has become important for a wide range of real-time applications, including real-time event detection, topic detection or disaster and emergency management. These applications require to know the precise location of the tweets for their analysis. However, approximately 1% of the tweets are finely-grained geotagged, which remains insufficient for such applications. To overcome this limitation, predicting the location of non-geotagged tweets, while challenging, can increase the sample of geotagged data to support the applications mentioned above. Nevertheless, existing approaches on tweet geolocalisation are mostly focusing on the geolocation of tweets at a coarse-grained level of granularity (i.e., city or country level). Thus, geolocalising tweets at a fine-grained level (i.e., street or building level) has arisen as a newly open research problem. In this thesis, we investigate the problem of inferring the geolocation of non-geotagged tweets at a fine-grained level of granularity (i.e., at most 1 km error distance). In particular, we aim to predict the geolocation where a given tweet was generated using its text as a source of evidence.
This thesis states that the geolocalisation of non-geotagged tweets at a fine-grained level can be achieved by exploiting the characteristics of the 1\% of already available individual finely-grained geotagged tweets provided by the Twitter stream. We evaluate the state-of-the-art, derive insights on their issues and propose an evolution of techniques to achieve the geolocalisation of tweets at a fine-grained level.
First, we explore the existing approaches in the literature for tweet geolocalisation and derive insights on the problems they exhibit when adapted to work at a fine-grained level. To overcome these problems, we propose a new approach that ranks individual geotagged tweets based on their content similarity to a given non-geotagged. Our experimental results show significant improvements over previous approaches.
Next, we explore the predictability of the location of a tweet at a fine-grained level in order to reduce the average error distance of the predictions. We postulate that to obtain a fine-grained prediction a correlation between similarity and geographical distance should exist, and define the boundaries were fine-grained predictions can be achieved. To do that, we incorporate a majority voting algorithm to the ranking approach that assesses if such correlation exists by exploiting the geographical evidence encoded within the Top-N most similar geotagged tweets in the ranking. We report experimental results and demonstrate that by considering this geographical evidence, we can reduce the average error distance, but with a cost in coverage (the number of tweets for which our approach can find a fine-grained geolocation).
Furthermore, we investigate whether the quality of the ranking of the Top-N geotagged tweets affects the effectiveness of fine-grained geolocalisation, and propose a new approach to improve the ranking. To this end, we adopt a learning to rank approach that re-ranks geotagged tweets based on their geographical proximity to a given non-geotagged tweet. We test different learning to rank algorithms and propose multiple features to model fine-grained geolocalisation. Moreover, we investigate the best performing combination of features for fine-grained geolocalisation.
This thesis also demonstrates the applicability and generalisation of our fine-grained geolocalisation approaches in a practical scenario related to a political security threats. We show the effectiveness of using new geolocalised incident-related tweets in detecting the geolocation of real incidents reports, and demonstrate that we can improve the overall performance of the traffic incident detection task by enhancing the already available geotagged tweets with new tweets that were geolocalised using our approach.
The key contribution of this thesis is the development of effective approaches for geolocalising tweets at a fine-grained level. The thesis provides insights on the main challenges for achieving the fine-grained geolocalisation derived from exhaustive experiments over a ground truth of geotagged tweets gathered from two different cities. Additionally, we demonstrate its effectiveness in a traffic incident detection task by geolocalising new security incident-related tweets using fine-grained geolocalisation approaches.
The use of social media in particular twitter has brought the world into becoming a global village. The platform is open to everyone using a smartphone and any basic computer. Twitter is a micro blogging site on which public opinion is posted and responses by readers act as a test to their attitudes and at timesdemand to action physical or symbolic.Every tweet sent has a spatial dimension to it, of date,time and location. This geospatial dimension gives it relevance and importance .The essence of twitter is to create followers who are updated on the real time events in any part of the world.Human security variables are posted and discussed unfiltered regardless of how explicit it is. Each year voluminousnovel people subscribe to the twitter platform in Zimbabwe.Social media has transformed media systems, irrevocably altering dynamics of production, consumption, and dissemination (Walsh & O’Connor, 2019). Social media have also challenged information hierarchies, opened up access and produced an entirely new ecosystem of information exchange (Pandalai, 2016).In the past years, tweeter’sessence of updating real time events has been shifting towards driving a hidden political and social agenda. Twitter has become a vocal sound that reach millions at the touch of the button. Politicians no longer need to hold rallies but just tweet their memorandum to a ready audience spread out over an eclectic geographical area. Similarly regime change proponents adopt the same modus operandi. Through the use of twitter, citizens are empowered as subjects ofcommuniqué who can directly shape public discourse and opinion. Only twitter software owners have the mandate to stop or block a user from accessing an account if the content is flagged unsuitable by a multitude of other twitter users. The location of tweets can be mapped according to language and messages being broadcast at the time. A Global position system (GPS) of a tweet can be determined using dedicated softwares. Over-sharing of information on twitter increases exposure of location-based information, thus posing a threat to citizens’ privacy (Rose, 2011). Several theories have been propounded to help in understanding the threat posed by twitter to the socio-economic wellbeing of citizens, in general, and the national security, in particular. This paper was mainly informed by two sociological theories, namely; the social movement theory and the social responsibility theory.
.This research is therefore situated in the context of establishing a link between how geolocation of harmful tweets could be used to manage political security threats associated with the use of twitterin Zimbabwe.
In an epoch of globalization, the mist of improbability lurks in every country’s territory and Zimbabwe is no exception, it faces a wide spectrum of threats and challenges varying from political, military, economic, social, information and infrastructure. These problems are compounded by the continued developments in Information and Communications Technology (ICT) especially the proliferation of anonymous tweeter handles and trolls. Irresponsible use of social media has resulted in social vices such as violence, terrorism, child pornography and a myriad of other social ills. Twitter platform has been used to instigate violent protests and issue subversive statements, causing fear and despondency amongst citizens. Tweeter platform has also been used to facilitate other crimes such as human trafficking and distribution of pornographic material. While several existing statutes have been raised in the face of these threats, the absence of a specific law to deal with social media threats militates against the current legal framework. The anonymity of some users pose greatest challenge in the quest of identifying the true nature of the perpetrators. There is not much documented evidence of the impact of social media especially twitter on the broad national security discourse in both the developed and developing world. Terrorist organisations such as al Qaeda and the Islamic State of Iraq and Syria (ISIS) have been using social media to recruit (Kimutai, 2014; Liaropoulos, 2013; Pandalai, 2016) and to radicalise citizens (AlZaabi&Tomic, 2018) .During the 2011 England riots, teenage gangs used social media communication platforms to evade authorities, publicise lawlessness and coordinate anti-social behaviour (Fuchs, 2013). Through social media activists are able to overcome censorship, coordinate protests, and spread rumour with ease in instances where regimes stifle dissent and try to control public discourse (Tufekci, 2017).
Twitter has been instrumental in the spread of fake news, with the intent to cause fear and panic among citizens. Fake news, defined as news which is wholly false or containing deliberately misleading elements incorporated within its content (Bakir&McStay, 2018), is widely circulated online. Fake news that is propagated through twitter can have implications on the politicalwellbeing of a nation. People lose hope in the Government because of the supervened confusion from deceptive tweets. People in other locations may be misled to think that riots are happening in another part of the country compelling others to join when in actual fact it is a hoax. For example, in 2013, the Associated Press’s Twitter account was hacked and released a tweet falsely claiming that there had been two explosions at the White House and that the United States of America President Obama had been injured (Forster, 2013). Within 2 minutes, the tweet had reached United States stock traders and the Dow Jones dropped over 143 points (a $136.5 billion loss). Although the tweet was discovered to be erroneous and taken down within minutes, the damage had been done. Parody accounts cause despondence as people struggle to determine which one is the original account and which one is fake.In Zimbabwe the most used twitter accounts belong to Nick Mangwana, George Charamba and Nelson Chamisa, people literally accept as true posts from these accounts. The parody accounts of the twitter handles usually stir up people’s emotions.
Based on the literature discussion presented in the background to the study, the problem statement reads as ‘there has been a proliferation of harmful tweets that pose a serious political security risk, but so far no one has uncovered the spatial characteristics of these tweets making it difficult to develop effective counter measures.’ From this problem statement, this study proposes to pursue the following empirical research questions:

• How can geospatial technologies be harnessed to geolocate tweets that pose a political security risk?
• Do these tweets have a detectable spatial pattern in Zimbabwe?

To achieve the above stated questions, the following specific objectives will be pursued:
• To map the geolocation of harmful tweets in reference to Zimbabwe political security.
• To determine the impact of clustered or spaced tweets to Zimbabwe’s political security.
• To identify various trends and patterns that act as pointers to threats that need swift countering?

This study is significant in that it is bent on observing the pattern and relation of various tweets and how they impact on political situation of Zimbabwe. The study will give national security practitioner’s insights to critically assess the effectiveness of their programs and policies at national level with the aim of upholding political security at core. This project will be helpful in the establishment of effective methods and programs that will enhance political security in Zimbabwe.
The research has an effective political security fortification thrust through recognition of the potential coercions from random harmful tweets. It is through appropriate policy recommendations and advice such as those that emanate from this study that this potential can be comprehended by the nation at large. The tangible aspects of the products of this research can be summarized below:
– A policy paper that will illustrate and map the link between geolocation of harmful tweets and how they pose a challenge to political securityin Zimbabwe.
– An academic paper that contributes towards a better understanding of National Security Policy and twitter use in Zimbabwe, and –
– Most important of all, the research publication will add to the scarcely available literature on the link between geolocation and harmful tweets in relation to political security in Zimbabwe.

This research is not without some limitations which include the following:
• There is bound to be reluctance of some twitter users to disclose their personal information in the event of not trusting the researcher. However, since the researcher had been exposed to geospatial intelligence and ICT, the research will use that as an advantage to extract information from them.
• There is very little published literature about the link between geolocation and harmful tweets in relation to political security in Zimbabwe, hence the researcher will be forced to rely mostly on interviews with key informants which can be biased at the end of the day.
• Financial and technological constraints as well as transport problems might affect the researcher to do some research as expected. The cost of buying data bundles is a challenge. As such the research shall exploit available electronic and printed information about the topic under research.
The research is mainly centered on Zimbabwe especially Harare. The number of people using twitter in Zimbabwe has been growing exponentially. Harare has the widest robust network coverage. The criteria for selection of time frame included in this study were based on the discretion of the researcher reliant on his previous knowledge of twitter and the network coverage of Harare.
The researcher observed anonymity, confidentiality and secured informed consent from the participants. The researcher did not make deliberate errors of omission and commission in order to misrepresent phenomena. The researcher had fair selection of participants, respect for the dignity of the same and avoidance of deception at all costs. The special right for the study was always provided for.

1.9 Definition of key terms
Geolocation is used to identify and monitor the locations of connected devices using location techniques such as GPS or IP. As these devices are mostly used for the purpose of tracking and monitoring the movement and position of people.
Twitter is a microblogging site for free social networks, which allows registered users to broadcast tweets. Via multiple channels and devices, members can broadcast tweets and follow tweets of other users…. Twitter’s default configuration is public.
Political Security
Political security is the defense against any form of political oppression. It is concerned with whether people live in a society that honors their basic human rights.
This research contains five (5) chapters that contribute towards the realization of the objectives set out by the researcher at the commencement of the research exercise. Below is a brief outline of each chapter
The chapter includes the complete introduction of the study on the link between geolocation of harmful tweets and the political security in Zimbabwe .It constitutes the research background outlining the historical context, problem statement,objectives, research questions,assumptions, ethical consideration and the significance of the study. It concludes by focusing at the delimitation of the study and limitations of the study
The chapter considered the work that has already been done by other scholars relating to understanding how geospatial location of harmful tweets link with political security of Zimbabwe. Theoretical framework and conceptual framework is also included in this chapter in order to address issues to do with the conduct of the research objectives.
The chapter focuses at the cyber space particularly twitter, thegeolocation of harmful tweets in relation to political security in Zimbabwe. Qualitative and quantitative methods are used in this research.
The Data collected statistics and other general information will be presented using graphs in analysing research findings dealing with the link between geospatial location of harmful tweets and political security of Zimbabwe.
The lastchapter summarizes the research findings, gives a conclusion and proffers recommendations to the link between geolocation and harmful tweets contribute to the political security issues in Zimbabwe. . The chapter ends with a list of references.






Chapter 2 – Literature review
2. Introduction
Twitter reportedly facilitated post-election protests in Iran and Moldova in 2009 and it is credited for the revolutions that took place in Egypt, Tunisia and other Middle East and North African countries in late 2010 to 2011 (Starbird & Palen, 2012; Aouragh & Alexander, 2011; Shirky, 2011; Mungiu-Pippidi & Munteanu, 2009). Tellingly, these political upheavals in 2010 – 2011 have been dubbed “Twitter Revolutions” (Shirky, 2011).
The so-called “Twitter Revolutions” preceded the important harmonized elections in Zimbabwe in 2013 and it was anticipated that social media was similarly going to play a major role (Ntuli, 2013). In addition to this, the media and the political environment in Zimbabwe encouraged political participation through social media as the mainstream media had been muzzled by the government through legal instruments such as the Access to Information and Protection of Privacy Act (AIPPA).
The development of the media (print, broadcast and social media) has a bearing on how new media platforms, such as Twitter, are utilized. It is thus significant to take a historical, descriptive and critical look at media in Zimbabwe as it gives a firm foundation to the present analysis. It is necessary to look at relevant literature tackling issues such as media control by the state, the legislation and policies governing media, media ownership patterns, media diversity, how technology impacted Zimbabwean media as well as state – media relations.
A simple internet search shows that significant literature on Twitter was produced starting with Java, Song, Finin and Tseng (2007). Notably, Java et al (2007) produced their ground-breaking work only a year after the micro blogging site was launched. Attention to the platform was honed by propositions that Twitter was so influential that it “caused revolutions” (Starbird & Palen, 2012; Aouragh & Alexander, 2011; Shirky, 2011; Mungiu-Pippidi & Munteanu, 2009) only three years after its launch in 2006 (Rodgers, 2014) in the case of Iran and Moldova and less than five years in the case of the Arab Spring. Such optimism, understandably, makes the study of Twitter an exciting enterprise.
Inevitably, a range of studies, papers and books were written about the micro blogging platform. Unfortunately, for this project, these researches have largely been concentrated specifically on the Middle East and North Africa (MENA) nations. Scholars outside African institutions provide the lion’s share of these studies. Sub-Saharan Africa appears to have been omitted from the growing body of research on the trending social media platform. The dearth of researches does not suggest that the micro blogging platform is not used as there are media reports and analyses on its use in business, politics and social interaction (see for example Noonan & Piatt, 2014; Dahlberg, 2013a).
Research on how Twitter facilitates political participation in Zimbabwe is rare. This paucity, to some extent, is a reflection of how scholars tend to take up studies on issues in the country. Research on Zimbabwe, post-1980, can be divided into three categories namely: those analyzing the transition of government power, pressure of democratization, and authoritarianism in the country (Laakso, 2003:1). These three categories fall within three, but overlapping, periods. The periods are: consolidation of power of the ruling party during the 1980s, World Bank and the International Monetary Fund sponsored economic liberalization in the 1990s and deepening economic crisis since the turn of the century. In the first few years after independence, the majority of scholars focused on political economy, for example, Mandaza’s (1986) Zimbabwe: The political economy of transition – 1980 – 1986.
What is telling from the articles in the volume is that they shied away from political topics and chose to focus more on economic transition. This meant that the “very repressive government reactions to opposition or criticism were not in research during the first decade of independence” (Laakso, 2003:1). This changed towards the end of the first decade of independence, mainly because of internal transformations (the unification of the two main political parties Zanu PF and PF Zapu and the ensuing efforts to establish a one-party state) and external pressures, especially the end of the Cold War. In response to changes within the country and the external developments, the research focus shifted to addressing issues of democracy, especially towards the 1990 elections (see Mandaza & Sachikonye, 1991; Banana, 1989).
The 1990 elections created a lot of excitement and surprisingly, Moyo (1992), in a detailed study of the polls, only mentioned the media in passing. This is unlike what Makumbe and Compagnon (2000) did with reference to the 1995 polls, where they devoted an entire chapter to the analysis of the role of the media in the elections. Stellenbosch University https://scholar.sun.ac.za 33 Subsequent studies undertaken have focused on the role of the media in the 2000, 2002, 2005 and 2008 elections (Mutsvairo, 2013; Waldal, 2005).
2.1 What is Twitter?
2.1.1 Background to Twitter
When launched in 2006, Twitter was considered an urban lifestyle tool for updating friends on one’s whereabouts (Rodgers, 2014: X). It was originally designed that tweets were to be shared via short messaging services (SMS) and thus were limited to 140 characters (Boyd, Scott & Gilad, 2010). Until 2009, the platform asked its users: What are you doing? (Rodgers, 2014: XII). The platform users understandably answered this question in a way that led many who studied Twitter to conclude that the content on the platform is mundane, banal and phatic (Rodgers, 2014) or creating a noisy environment. The change of the question to users to: What is happening? shows that the micro blogging platform was focusing more not on the individual but what is happening around them. Interestingly, these changes were effected in 2009 (Rodgers, 2014) the year when for the first time it was suggested that the protests in Iran and Moldova were “Twitter revolutions”.
2.1.2 How Twitter has evolved since 2006
Writing about the micro blogging platform more than eight years after inception, Weller, Bruns, Burgess, Mahrt & Puschmann (2014) give an interesting account of how the platform hastransformed communications. The title of the book, Twitter and society, is evidence that the authors acknowledge the platform’s impact on society. In the chapter introducing the work, the authors trace the path that the micro blogging platform has trodden since 2006. Weller et al (2014: XXIX) posit that alterations to the platform have not changed the basic idea behind the service, that is, “users may post short messages of up to 140 characters and follow updates by other users”.
As Twitter users embraced the “technology and its affordances, a series of new conventions emerged that allowed users to add structure to tweets” (boyd et al, 2010). Twitter users developed ways to reference other users, converged on labels to indicate topics (hashtags) and devised language to propagate messages (boyd et al, 2010). Resultantly, the new structure has encouraged the formation of a complex follower network with “unidirectional and bidirectional connections between individuals, but also between media outlets, NGOs and other organisations” (Weller et al, 2014: XXX).
It is apparent that Twitter has become an important tool for communication and it is not only used by individuals but business entities and not for profit organisations as well. Weller et al (2014: XXX) go on to argue that “Twitter is increasingly used as a source of real-time information and a place to debate news, politics, business and entertainment”. This means that the networks that emerge from the use of Twitter bring entities with different capacities together. It is evident that the platform has altered the media ecology.
However, it is important to further question if the openness of the platform, which makes large NGOs participate as equals with individuals, empowers previously disadvantaged groups. This helps one to ascertain if all users have equal access. Access to Twitter, though open, is dependent upon a number of factors, including having the right technology, basic literacy, knowledge of how the platform works, and the ability to join existing networks. It is also important to acknowledge how social media platforms have incorporated changes and harnessed communications in an effort to monetise the data (Langloes & Elmer, 2013:2).
Changes in Twitter’s outlook and “this shift has been realised materially in the architecture of the platform including not only user interface, but also affordances of its API and associated policies affecting the ability of third-party developers” (Puschmann & Burgess, 2013: 3-4). This has seen the firm changing policies regarding access to data as it continues to ring-fence its treasure trove and limit third party access to the archived tweets (Bohn, 2012). This is made worse by the fact that the public can access tweets that are a maximum 10 days old (University of Cornel, 2015), raising Stellenbosch University compelling and pertinent questions on who owns the content that is produced on the platform. In addition to adopting user initiated innovations that the platform has incorporated,
Twitter has also responded to the need to enhance communication through the platform by developing tools that allow users to evade censorship (Twitter-Blog, 2011). Important to mention, however, is the point that users have generally benefitted from the spinoffs from instituted changes. Twitter has worked hard to get more users as big data means more revenue from advertisers. As further proof, the platform listed on the NYSE in 2013 (Oran & Shih, 2013), in the same way as other Web 2.0 companies such as Facebook, showing that it is a business and that the pursuit of profits could have driven these changes. Twitter also plays to the whims of the powerful, for example in 2009, it was asked to postpone its scheduled maintenance for Iran servers by the United States government and it obliged (Guardian, 2009).
This was at the height of the protests in Iran and it is speculated that it obliged so that the use of the platform could ignite more protests. In the case of this research, there were no significant business decisions taken by Twitter that had an impact on the collection of tweets during the 51 day period. 2.2.3 The use of #, @mention and retweet (RT) on Twitter Studying Twitter entails coming up with methods of “capturing” tweets and as argued in Chapter 1, one way of doing so is through the use of hashtags.
In a very insightful presentation, Bruns and Burgess (2011:3) underline the importance of the hashtag as a “central mechanism for the coordination of convergence on Twitter”: Hashtags are vital for a conversation on Twitter because they allow users to follow posts thus enabling users to: Communicate with a community of interest around the hashtag topic without necessarily needing to go through the process of establishing a mutual follower/followee relationship with all or any of the other participants. (Bruns & Burgess, 2011:3)
It is possible for anyone with a Twitter account to be able to follow a hashtag and communicate with other users even if they do not follow each other. Twitter’s privacy settings allow a user to block another user so that they will not be able to see their tweets. This does not affect hashtagged tweets when searched for by using the Twitter search engine. It thus facilitates conversation with anyone interested in the topic. Additionally, it is also possible to search hashtagged tweets even if one is not a Twitter user.
Hashtags make it easy for users to respond to breaking news or new development of a topic of interest and as Bruns and Burgess (2011: 3) point out, “…new hashtags can be created ad hoc, by users themselves, without any need to seek approval from Twitter administrators”. The freedom to create a hashtag enables users anywhere in the world to address a topic be it of local or international significance. This echoes the postulations by the advocates of a network society who argue that those with the necessary tools can broadcast content from anywhere at any time.
While this may be taken as an advantage, it also has a downside as it is possible that those contributing to the hashtags may not be affected by the topic under discussion. For example, it could be someone tweeting from a remote location with no real attachment to what is happening in Zimbabwe (see Addendum C & D showing the location of those who tweeted on the elections in Zimbabwe using the four hashtags). While Bruns and Burges (2011) prepared a very informative article giving some important insights, it falls short of clearly explaining how conversation takes place on Twitter.
The major question which remains unanswered is: Does it mean if one uses a hashtag, they have entered a conversation? In addition to failing to address this question, the two authors make a very simplistic assumption, that by creating a hashtag, users will naturally join the “conversation”. Additionally, a tweet by one with many followers is likely to be noticed more than one with a few followers. Some Twitter users are likely to post more than others, which means that the conversations if they are called that, are not done in the normal way that everyday conversations take place.
In addition to this, users may not know which hashtag to use and others may not be using hashtags at all. In so doing, they may be considered outside a conversation when in fact they may be using certain keywords related to the topic. Finally, the use of hashtags, while commendable, suggests prior knowledge of the discussion or topic, which means those not aware may be sidelined. This raises questions on who initiates a hashtag and makes it popular or acceptable over other competing hashtags. This issue is not discussed in the article by Bruns and Burgess (2011). This may explain why we have as many as four hashtags for the same event, that is, the 2013 harmonised elections in Zimbabwe.
In another interesting article Messina (2007) argues that: A drawback to the ad hoc and non-supervised emergence of hashtags is that competing hashtags may emerge in different regions of the Twittersphere or some hashtags may be used for vastly different events taking place simultaneously. Thus while the hashtag is a very powerful affordance that comes with Twitter, its Achilles heel is that without centralised control, there are chances that many hashtags can mean different things and the same one can mean different things to different people. This poses a danger to any researcher as they have to be sure that they are collecting tweets which are related to the topic they are studying.
2.1.3 What constitutes a Twittersphere or is it a community?
The affordances brought by Twitter allow users to create a community and at the same time make sure that there is an audience that is following the topic under discussion (echoing the supposition that there is an emerging network). This clearly lays a firm foundation for horizontal communication, brought about by the affordances embedded in Twitter, including the use of the hashtag, the @reply and retweeting, possibly facilitating communication between two or more people without any mediation, (in most cases it is from one to many as anyone has access to information that is published on Twitter).
2.2 How does Twitter facilitate political participation?
From 2009 (after the April Moldova and June Iran post-election uprisings) to the Arab Spring, there has been a cacophony over what role, if any, Twitter played in the unrests. Opinion is divided between those who saw a positive influence of Twitter during the revolts to the extent that these Stellenbosch University https://scholar.sun.ac.za 39 are called “Twitter Revolutions” and those who dismiss it. By extension, authors who support this viewpoint fall within the cyber-optimists category, as briefly discussed in Chapter 1.
Some authors, however, argue that there were no “Twitter Revolutions”, accusing scholars, journalists and activists of playing up the role of Twitter despite glaring facts on the ground which show otherwise. The Arab Spring and the post-election protests in Moldova and Iran have induced a surge in researches on the role of Twitter in facilitating political participation. The focus on the role of Twitter in political participation by researchers has enriched our understanding of this subject but it is not an exhaustive focus.
Equally important and related to this subject matter is research on how Twitter facilitates political participation in other parts of the world or different political contexts, for example in Zimbabwe. Whereas the Arab Spring in late 2010 and early 2011 could be credited for bringing to the fore the role of Twitter in facilitating political participation, it is important to mention that debates about its role preceded and even outlived these events (Varnali & Vehbi, 2014; Hosch-Dayican, Aurit, Aarts, & Dassen, 2014; Simões, Carmo Barriga, & Jerónimo, 2011; ). Research only spiked with the unexpected events in the MENA countries and there is a danger that when researching this topic one focuses only on the role of Twitter in the context of the so-called “Twitter Revolutions”.
It is thus important to widen the literature review and not limit it to the works on “Twitter Revolutions” and include works that look at how the platform facilitates political participation in other political contexts. It is remarkable to note that those scholars participating in the cyber-optimist versus cyberpessimist debate have all presented evidence to prove their standpoint. Noticeably, those who wrote immediately after the revolutions were bound to romanticise the role of Twitter and other social media while those writing with more time to reflect were more critical and not overly optimistic.
A good example in this regard is Wojceiszak and Smith (2014:92) who are clearly sceptical about the role of social media in causing revolutions which they say led to a “conviction that led to attractive monikers such as ‘Twitter/Facebook Revolutions’”. The problem in analyzing the part played by social media in the Arab Spring is that there are very few analytical tools. Additionally, what happened then was very new, catching analysts by surprise. Scholars and journalists used weak and at times archaic toolkits to explain what was happening within a few weeks of the fall of the Tunisian and Egyptian regimes only to reflect latter in a more soberly 40 manner.
Alterman (2011:104) finely captures and outlines the logical fallacies which informed scholarship and media reportage on the Arab Spring and these include:
1) Arguing that since the diffusion of the internet in the MENA countries is new and the new movements that emerged used the internet, therefore the advent of the new ICTs caused the revolutions.
2) The internet is mainly in English, thus outside observers can follow what is happening and can empathise with the English speakers who are appealing for their help thus the outside world should pay attention.
3) Western social movements use the internet and if it works for them then it should work for everyone else.

4) The Arab internet narrative has attractive heroes, youthful, English speaking and full of energy, unlike the terrifying images of the likes of Osama Bin Laden which had come to be associated with Arabs. As such, these should be connected with and be helped to effect political changes in their countries.
5) The West has cosied up to autocrats in MENA thus the new narrative of the revolutions (made possible by Western technology) relieves them of the burden of guilt they felt for allegedly working together with the strongman in the MENA countries against the people.
These logical fallacies may, to some extent, explain some of the simplistic conclusions that were made especially by the media as the revolts broke out in Tunisia and started spreading across the Middle East and North Africa. It is also important to note that these fallacies may not be limited to MENA countries but across the globe. Some of the cyber-optimists ignored the role of the traditional media and other grassroots organising methods and thus prematurely declared that social media had caused the revolts.
Alterman (2011) takes a very critical approach and even dismisses those seeing the role of social media as important to Western scholars and not the people on the ground. Building on the growing septicism about the romanticised role of Silicon Valley technologies in facilitating public political participation, including allegedly toppling regimes, this research seeks to take an objective look at the collected data in order to find out how Twitter was used during the 2013 elections.
Amongst the flood of research papers explaining the role of social media in the Arab Spring, there were scholars who chose to be ambivalent without siding with either the cyber-optimists or the cyber-dystopians. Aouragh and Alexander (2011:1345) argued that the turmoil that was taking place in the Arab world “presented an opportunity to finally test theoretical assumptions about the internet” as the revolts “have become a social lab offering us the kennel of material”. This was a call for more detached observation with an objective analysis of the situation that avoids falling into the pitfalls of taking a cyber-utopian or the cyber-sceptic slant. This approach is also supported by Christensen (2011) who argues that when considering the interplay between affordances and materiality, the socio-political context is important.
This is in line with the critical discourse analysis approach which encourages the use of different methodologies as well as the use of various sources of information to understand a phenomenon. In so doing, this research avoids the fallacies identified by Alterman (2011). In the process of balancing the opposing views of the cyber-optimists and the cyber-dystopians, it is important – also within a critical approach – to strive for balance and make use of analytical tools that give empirical evidence based on what has been studied. The presentations by Alterman (2011) and Christensen (2011) are appropriate to this study as they give a very firm analytical starting point.
2.3 Zimbabwean Twitter is shifting politics
An article by Partson Dzamara in News Day of 30 May 2018 showed the state of affairs in the twitter corridors. Partson wrote: “This article is written against a background of Zanu PF’s presidential candidate for the 2018 plebiscite, Emmerson Mnangagwa recently unleashing his party youths to be vigilant on social media, instructing them (Rakashai vanhu pa sosho media) “Clobber them on social media”. The President had told his youth supporters to be actively involved in the social media debates and defend the party ideology. This shows that the party was living up to the realities of the time. They had realised how powerful social media was in making political persuasions as well as furthering them.
Though opposition opponents like Partson Dzamara took it to mean that the president was encouraging violence on social media, it can be easily concluded that he was simply unleashing them to win debates on behalf of the party. According to an article by Jacquelin Kataneksza “It’s been claimed that ZANU-PF paid unemployed, computer literate supporters to flood social media platforms with attacks and counter-attacks targeted at overwhelming a poorly resourced opposition.” The authenticity of the above claim is debatable, but the fact that ZANU-PF had a crafted and coordinated social media crew is true.
They ran their accounts as individuals, but they would say almost the same thing from different fronts. The opposition, on the other side took a counter measure; they also stood to defend their movement. The ruling party’s “Varakashi” took on Chamisa supporters known as “Nerrorists” (after Chamisa’s nickname, Nero) in a series of online propaganda battles. The marked upsurge in the tactical use of inflammatory language, and fear mongering as well the distribution of fake news and doctored images, arguably buoyed some candidates while bringing others down.
On Election Day, all three platforms were used by people chronicling their voting experiences. And the violent aftermath of the election that left several people dead played out online even as it played out on the streets. There was a lot of information circulated on social media. Early morning on 01 August 2018 at 02:37 am, Nelson Chamisa took his message to twitter and said: “Thank you Zimbabwe… I’m humbled by the support you have given to me as a presidential candidate. We have won the popular vote. You voted for total change in this past election. We have won this one together, No amount of results manipulation will alter your will…#Godisinit.” (@nelsonchamisa)
At around 02:50 am on 01 August 2018 Chamisa posted the following on his twitter handle: “Winning resoundingly…We now have results from the majority of the over 10 000 polling stations. We’ve done exceedingly well. Awaiting ZEC to perform their constitutional duty to officially announce the people’s election results and we are ready to form the next gvt. #Godisinit”. On the same date 01 August 2018 at 1:09 pm, President Emmerson Mnangagwa also took to twitter and said “At this crucial time, I call on everyone to desist from provocative declarations and statements. We must all demonstrate patience and maturity, and act in a way that puts our people and their safety first. Now is the time for responsibility and above all, peace. (@edmnangagwa). The notion sent by Nelson Chamisa’s tweet was that election manipulation was likely and also that he had won the race, this was in violation of the Constitutional Act, which prohibits the premature announcement of election results.
This was an abuse of social media, a manipulation of the tool knowing very well that it was effective. As a media outlet, social media was used by both political parties in a biased manner. Tendai Biti41,42 was also embroiled in controversy as he held a press conference and allegedly announced that Nelson Chamisa had won the elections and also that ZANU-PF was in an attempt to rig and steal the election. The videos were sent on twitter and the masses were stirred. Some party hardliners like Happy more Chidziva took to twitter and invited party supporters to come at the party headquarters to celebrate the alleged victory. Social media contributed a lot to the happenings of the violent protests that erupted in Harare on 1 August 2018.
People were demonstrating against an alleged vote stealing and they wanted their preferred candidate announced and declared winner. Tempers were high, and a lot of unauthenticated news was circulating on social media. When the army was deployed, social media was awash with the news. People posted videos and photos of soldiers in action as well as of the victims. The news also spread and the international world got the story and they aired their views on the developments. The article argues that the rise of internet use, access to mobile phones and mobile network coverage offered hope for access to information, freedom of speech and association referred to above.
We also argue that social media platforms have challenges of unverified, exaggerated, unauthentic and sometimes fake content; consequently misleading citizens. People became intolerant of each other’s views on twitter, so much that it was no longer safe to air one’s views especially those contradicting the popular view. It became dangerous to belong to either side, there was a lot of verbal abuse and verbal attacks on opponents. This could also justify the existence of a lot of ghost accounts on twitter; it could be that people had to hide their identity for their safety.
The fear of reprimand, harassment and insults was also based on the statement issued by the Army Commander Lieutenant-General Phillip Valerio Sibanda published in The Herald of 5 August 2016. He said the following: “As an army, at our institution of training, we are training our officers to be able to deal with this new threat we call cyber warfare, where weapons, not necessarily guns, but basically information and communication technology, are being used to mobilise people to do wrong things. We will be equal to the task when the time comes.” The above statement sent a clear message that the security sector had also considered active involvement on social media political issues.
Their aim was to “deal” with this new threat as the Commander highlighted, and this shows that it could be very difficult to participate on political discourse on either Facebook or twitter. People had to hide behind fake accounts, and the fake accounts became cauldrons of various nefarious activities by both the ruling party and opposition party supporters. Hate speech, name calling and all sorts of denigrating behaviours have been manifested on social media.
Social media has also been critical in exposing corruption and bringing to light untold transactions and murky dealings of the elite and the big fish. Post July 2018 election, President Mnangagwa reiterated on his fight against corruption and any retrogressive behaviours that would cripple the economy. Corruption in Zimbabwe had reached alarming levels during the Mugabe era, and when President Mnangagwa declared war against it, people were willing to help him as well as to test the sincerity of his public statements against corruption.
William Mutumanje popularly known as Acie Lumumba in the political circles as well as on social media is among the social media warriors who took corruption expositions to social media. In a letter, Finance Minister Prof Mthuli Ncube announced the appointment of Lumumba on 20 October 2018as the new spokesman for his ministry. The letter was widely circulated on social media and was also widely criticised on social media. In no time, news went viral that Lumumba had been unprocedurally appointed and that his ouster was imminent. Lumumba took to Facebook and Twitter to expose people who were behind his sacking as well as behind the financial crisis in the land.
He alleged that Queen Bee leads a corrupt cartel that has captured some senior politicians, and named certain directors at the Reserve Bank of Zimbabwe (RBZ), claiming they were part of a syndicate causing untold suffering in the country. Consequently, and because of Lumumba’s revelations four directors at the central bank were suspended pending investigations. Lumumba’s story was widely believed, people started to question the sincerity of President Emmerson Mnangagwa and his government in its fight against corruption. This did not only expose corrupt cartels, it also exposed the state as well. Social media in this case was used to even influence the state to take action see. The above news site suggests that Lumumba’s social media antics had pressured the President to make the officials suspended through RBZ governor.
Social media again has been used to expose the rot in Public Service, with the latest being the corrupt engagements by Public Service Commission paymaster at the Salary Services Bureau, Brighton Chiuzingo, and general manager human resources only identified as E. Chigaba, on allegations of abuse of office and mismanagement. According to an article by Matthew Takaona. Brighton Chiuzingo, the chief paymaster at the Government Salaries Service Bureau (SSB) had been suspended from work without pay on allegations of making arbitrary allowance and salary increases of 40% for himself and collecting back pay of $6 600 backdated to January 2018.
This rot had been exposed by one Prisca Mutema on 06 December 2018 on her Twitter handle (@PriscaMutema2). She wrote “This is Brighton Chiuzingo, Zimbabwe Gvt Paymaster General. He is a thief & a major reason why gvt spends 95% of its budget just on salaries. He is also part of a cartel that involves the Registrar General’s & the Immigration Dept. The cartel’s business is fraud.” She further said “This is Ngoni Masoka, former PremSec in the Public Service Ministry & Chairman, Chief Corruptor & Godfather of (NSSA). Since 2014, these 2 have stolen millions of US$ thru gvt payroll & NSSA. He’s also reason 95% of gvt budget is spent on salaries. She went on a 14 thread twitter laying bare facts backing her exposition. The tweet had about 250 retweets from her twitter followers, and the issue was blown in a day. The Herald of 07 December 2018 carried a story to the effect that government had suspended Brighton Chiuzingo, a day after social media had blown the whistle.
This shows that the political narratives of the land have seen the coming in of a new player which is social media. Social media has been used for the fast spread of news in a way that leaves the traditional media outlets behind. News now spread faster through social media, and people have resorted to believing more on social media for news than any other source. As discussed earlier in the paper, Prisca Mutema who has exposed the Public Service rot is controversially believed to be a ghost account but revealing the sober truth obtaining in the country.
2.4 Geolocation: What is it
Geo-location services are online services that collect, provide and analyse geo-information. They are rapidly growing in popularity, and thus also in use. One example of these services is: Foursquare, where you can “check-in” using your current position and share this with other users. Other uses or types of applications are the ones that locate discount coupons for stores in your current geographical area. Today, many of the online sites or applications collaborate with third-party companies that also can take use of the geographical data you provide in these (Freni et al. 2010).
2.4.1 Geo-social network (GeoSN) structure
A geo-social network (GeoSN) is a traditional social network but with location capabilities. Figure 1 (Ruiz et al. 2011, p. 21) depicts the main concepts and the relationships.
As shown by the figure, we have a user, who simply is a person using a GeoSN. This user can in the traditional social network context build online relationship with other users. A GeoSN consecutively provides a further extension to such relationship by providing additional services. Users create relationships for the sake of capturing real-life relationship, to express their standpoint/feelings, e.g. putting a “like” on something on Facebook or common interests. Further, these can be symmetric e.g. friendship on Facebook or asymmetric e.g. to follow someone on Instagram.
In a GeoSN users commonly can share user generated content with the people they want to. More often, the user can choose with whom to share this content with, as with: all other users, or just with selected ones. The shared content may be associated with location i.e. geotagging and/or with other users, i.e. user tagging.
In a GeoSN users are located via a location update. There are two kinds of location update, check-ins (users update location at a predefined place) or via GPS or other similar service (users are tracked constantly or occasionally by a service that exploits the infrastructure of the communication for positioning the user). Both the content and the users can be associated with location and vice versa. Most GeoSNs are location-centric, which means they enable convenient content retrieval correspondent to the location. Examples of this are Flickr, where users can show photos on a map and the service of Facebook Places, which gives users information about who is in a particular location.

2.5 Conclusion
The review of related literature provided the investigator an overview of the research studies giving the theoretical framework on the present topic which in turn helped the investigator in planning a suitable methodology for the present study.
The next chapter will focus on the research design and methodology.




This chapter covers research methodology which will be organized under the following subheadings: Research design and locale, population, sampling techniques and sample size determination. Finally, it covers research instruments, pilot study, validity and reliability, data collection procedures, data analysis techniques.
3.2 Research philosophy
It has been noted that some writers use the terms ‘methodology’ and ‘method’interchangeably (Hussey & Hussey, 1997). They consider that methodology refers tothe overall approach taken, as well as to the theoretical basis from which the researchercomes, and that method is the various means by which data is collected and analysed(Hussey & Hussey, 1997). Similarly, Mason (2002) separates “the concept ofmethodological strategy” (2002: 30) from the method, while noting that a particularmethod will be a part of the strategy. In line with these writers, the approach taken hereis to include all facets of the research process under the overall heading ofmethodology. Therefore, the research design, the approach taken, the particular data collection methods chosen and the means of analysis, are all considered to be part of this thesis’s methodology, and are set out in the following sections.
However, underpinning the methodology, by necessity, is a philosophical stance in relation to the purpose and place of research in general, and this research in particular. A distinction that is frequently made regarding research philosophies is between positivism and interpretivism (Bryman & Bell, 2007; Hughes & Sharrock, 1997; Travers, 2001).
A central tenet of positivism is that researchers can take a ‘scientific’ perspective when observing social behavior, with an objective analysis possible (Travers, 2001). Bryman and Bell (2007) caution against assuming positivism and science are synonymous concepts, noting that there are some differences between a positivist philosophy and a scientific approach. They also note that there are some circumstances where an inductive strategy is apparent within positivist research, with “knowledge arrived at through the gathering of facts that provide the basis of laws” (Bryman & Bell, 2007:16). Nonetheless, research based on a positivist philosophy tends to be based on deductive theorizing, where a number of propositions are generated for testing, with empirical verification then sought (Babbie, 2005). Considerable data are often required as a positivist study would favor the use of quantitative methods to analyze large-scale phenomena (Travers, 2001). Inherent in this overall approach to research is the view that it is possible to measure social behavior independent of context and that social phenomena are ‘things’ that can be viewed objectively (Hughes & Sharrock, 1997)
In contrast, interpretivism tends to view the world in quite a different manner, requiring different response from researchers. As Bryman and Bell (2007) state, interpretivists take the view that:
The subject matter of the social sciences—people and their institutions—is fundamentally different from that of the natural sciences. The study of the social world therefore requires a different logic of research procedure (2007: 17).
This different logic within an interpretivism stance might prompt a researcher to use inductive theory construction, reversing the deductive process by using data to generate theory. Researchers would observe aspects of the social world and seek to discover patterns that could be used to explain wider principles (Babbie, 2005). In addition, it is seen that there is no one reality, rather reality is based on an individual’s perceptions and experiences (Robson, 2002). Linked to this position is the argument that the facets of the real world that are distinctly human are lost when they are analyzed and “reduced to the interaction of variables” (Hughes & Sharrock, 1997: 102). For this reason the role of the researcher should be to analyze the various interpretations that actors related to a particular phenomenon give to their experiences (Easterby-Smith et al., 2002).An interpretivism position was adopted in this research. That is, it is considered that there are multiple realities that make measurement difficult, and we can only seek to understand real-world phenomena by studying them in detail within the context in which they occur.

The researcher will use descriptive survey research design which describes the state of affairs, as they exist. This approach will be appropriate because the study involves fact findings and inquiries of the Establishing how geolocation of harmful tweets could be used to manage political security threats associated with the use of twitter in Zimbabwe. It aims at obtaining, information from a representative selection of the population from which the investigator presented the findings as being representative of the population as a whole. According to Orodho (2005), descriptive survey studies will be designed to obtain pertinent and precise information concerning the current phenomena and where possible draw valid general conclusions from facts discovered. The techniques that will be used in the field will be qualitative and quantitative.
Qualitative paradigm will be through open-ended questions and close-ended questions. In qualitative analysis, the information gathered will be structured along themes or categories as they occur in the questions. These allow for coding of the data for easy analysis.
The study will focus on what is commonly known as Zwitter which is Zimbabwe’s Twitter columns, with main reference to Harare. Singletor (1993) notes that, the ideal setting for any study should be accessible to the researcher and that which permitted instant rapport with the informants. Gwanda District is accessible.

Orodho (2005), defined target population as members of a real hypothetic set of people, events or objects the researcher wished to generalize the result of the research on. The target population will be politicians, policymakers, government officials, security sector and intelligency personnel.
According to Orodho (2005), sampling is defined as a means of selecting a given number of subjects from a defined population as a representation of that population. The population will be stratified into categories of the offices held by the respondents. From these strata, a representative sample will be drawn. Sampling will be used to identify one pilot community among among the communities in Harare. Simple random sampling will be used on the politicians to get the 11% respondents to fill the questionnaires. The criteria for selecting office bearers will be purposive where there will be more than one stream. Professional experience will be needed as a criterion for selection of the respondents. Analysis will be however based on only 11% and 100% of the respondents and office bearers who participated respectively. This will be done to enhance reliability. In mixed situations, the researcher will ensure gender balance by selecting equal number of men and women per community through random sampling that adapts.

Data collection instruments refer to devices used to collect data such as questionnaires, tests, structured interview schedules and checklists (Seaman 1991:42). Polit and Hungler (1997:466) define a questionnaire as “a method of gathering information from respondents about attitudes, knowledge, beliefs and feelings”. The questionnaire was designed to gather information about adolescent mothers’ knowledge, attitudes and beliefs regarding contraceptives.
The research instrument used in this study will be basically questionnaire. In addition, an observation checklist will be used to complement the questionnaire and bridge the gap in case there will be any inadequacy on either research tool. These two instruments will be both personally designed and developed by the investigator.
Questionnaires will be the main instruments for data collection in the study. Four different questionnaires will be used to collect information from twitter users, ministry officials, heads of security department and service chiefs. According to Orodho (2005), questionnaires offered considerable advantage in the administration; again they presented an even stimulus potentially to large number of people simultaneously and provided the investigation with an easy accumulation of data. Some of the merits of questionnaires will be low cost, freedom from interviewer’s bias as answers will be in respondent’s own words and that gives respondents adequate time to give well thought out answers. The items generated for the study will be both open and close ended types. The open ended items give the respondents greater freedom of expressing their own ideas and opinions, and give suggestions where necessary. Semi structured (open ended) questions elicits a lot of good qualitative data. The close ended items enable the researcher to obtain specific responses from the respondents. Questionnaires will be used to collect information that will not be directly observable as they inquire about feelings, motivation, attitudes, accomplishments as well as experiences of individuals.
According to Orodho (2005), it will be necessary that research instruments be piloted as a way of determining validity and reliability of the very tools to be used. The researcher will conduct a pilot study in one online community. Questionnaires will be administered to ministry officials and individuals on twitter. The observation schedule will be applied as well. The purpose of piloting will be to pre-test the research instruments and also familiarize the researcher with the data collection procedures. From the data collected, the instruments will be corrected and prepared for the final study.

Mugenda and Mugenda (2003) defined the term validity as the degree to which results that will be obtained from the analysis of the data actually represented the phenomena under study. Piloting will be done to check the questionnaires’ content, structure, sequence, meaning and ambiguity of questions. Content validity will be to some great measure ascertained by giving out instruments to professionals such as the researcher’s supervisors and colleagues to determine whether the instruments did measure what they purported to measure.
Mugenda and Mugenda (2003), defines this term as a measure of the degree to which a research instrument yields consistent results or data after making repeated trials. Reliability refers to consistency of measurement. The more reliable an instrument will be, the more consistent the measure. The researcher purposefully selected one pilot twitter community to test the reliability of the questionnaires through test-retest techniques. In case of misunderstandings or failure to generate results towards the purpose of the study, the affected questionnaire will be revised.
3.6.1. Logistical and ethical consideration
Mugenda and Mugenda (2003), in their book stated some considerations worth putting into practice by the researcher and the respondents during the research process. For instance, during the research process, the researcher will not ignore pertinent issues. He has also to express design in his study as well as value the use of his tests. The researcher will avoid misusing the privileges accorded to him. Plagiarism and fraud will be shunned at all cost during the course of the study. On the other hand, care will be taken not to use a special population amongst the respondents and those who appear to offer voluntary consent. Also, care will be taken by the researcher to guard respondents against physical and psychological harm. Again, cases of anonymity and financial issues will not be allowed to be the preserve of the respondents. Finally, dissemination of findings and any academic freedom whatsoever will be fundamentally with the researcher and not shared anyhow with the respondents.
3.6.2. Actual data collection procedures

An introduction letter from the University will be obtained to enable the researcher to administer questionnaires to twitter users, ministry officials and the other respondents in the selected cases. The researcher will then personally visit the respondents to have a rapport with the respondents as well as undertake to understand the environment. The researcher will again sensitize respondents on what will be done. As for the ministry officials’ heads of departments and service chiefs’ questionnaires, the researcher will give them out and collect them after one day; whereas for the questionnaires, the respondents will be chosen through simple random sampling to fill the questionnaires. The researcher will personally administer the questionnaire whose details will be filled in within a seating as provided for by each independent twitter user visited by the researcher. The observation schedule will also be administered on the sampled users prior to actual data collection, to provide first-hand information to the researcher on the resources within the environment of the users identified for study.

The data will be gathered, validated, edited and then coded; which consists of qualitative and quantitative data. The analysis will be done qualitatively.

This chapter has discussed the research methodology. The chapter presented the research design, sample and sampling procedures, data collection procedures and data collection methods. Data analysis and presentation was also highlighted in this chapter. Chapter four will focus on the presentation analysis and interpretation of data gathered and discussion of findings.






This chapter discusses the data analysis and findings ON Establishing how geolocation of harmful tweets could be used to manage political security threats associated with the use of twitter in Zimbabwe. The research objectives were to;
• To map the geolocation of harmful tweets in reference to Zimbabwe political security.
• To determine the impact of clustered or spaced tweets to Zimbabwe’s political security.
• To identify various trends and patterns that act as pointers to threats that need swift countering?
4.1 Demographic data of Social Media Users in Zimbabwe

The researcher first requested for data on the users of Social media in Zimbabwe to get a better appreciation of the access to social media by Zimbabweans. The results from statcounter website are displayed in Fig 4.1 above. In the diagram, it can be noted that Twitter commands a considerable following by Zimbabwens after Facebook and Pinterest.
The statistics in terms of comparisons are shown in table 4.1 below
Statistics on Social Media Usage Percentage in Zimbabwe: Table 4.1
Date Pinterest Facebook Twitter YouTube Instagram Tumblr LinkedIn reddit VKontakte Other
2020-02 31.9 28.82 22.94 4.32 11.66 0.2 0.06 0.05 0.06 0
2020-03 29.17 30.02 23.39 4.5 12.35 0.26 0.14 0.06 0.08 0.02
2020-04 27.25 23.2 22.7 6.2 20.11 0.19 0.18 0.12 0.05 0
2020-05 40.19 33.13 16.81 7.52 1.22 0.41 0.35 0.27 0.06 0
2020-06 38.04 35.14 16.15 7.46 1.49 1.14 0.28 0.25 0.04 0
2020-07 37.41 33.74 17.66 8.36 1.3 0.88 0.25 0.38 0.03 0
2020-08 35.53 31.17 22.88 8.02 1.35 0.44 0.22 0.31 0.06 0
2020-09 38.45 25.93 26.46 6.65 1.09 0.68 0.44 0.25 0.02 0
2020-10 40.92 28.23 22.76 6.06 1.14 0.34 0.33 0.15 0.06 0.02
2020-11 27.6 28.58 37.42 4.66 0.84 0.31 0.29 0.22 0.07 0.01
2020-12 39.67 30.8 22.63 4.87 1.37 0.28 0.21 0.12 0.03 0
2021-01 29.2 29.78 33.83 4.95 1.57 0.24 0.23 0.16 0.02 0.02
2021-02 28.92 32.81 30.17 5.1 2.21 0.15 0.35 0.22 0.05 0.02
The statistics show that Zimbabweans have access to social media platforms especially Facebook and Twitter. These are the platforms were harmful messages are posted by many politicians. Once the researcher established the usage of social media in Zimbabwe, he sought to identify the number of internet users in Zimbabwe.
In an interview with Telone Internet Provider, the researcher was appraised of the following internet dynamics;
4.2 Internet users in Zimbabwe
• There were 5.01 million internet users in Zimbabwe in January 2021.
• The number of internet users in Zimbabwe increased by 203 thousand (+4.2%) between 2020 and 2021.
• Internet penetration in Zimbabwe stood at 33.4% in January 2021.

4.3 Social media statistics for Zimbabwe
• There were 1.30 million social media users in Zimbabwe in January 2021.
• The number of social media users in Zimbabwe increased by 320 thousand (+33%) between 2020 and 2021.
• The number of social media users in Zimbabwe was equivalent to 8.7% of the total population in January 2021.

The number of Social Media users in Zimbabwe puts a large number of people at risk of accessing harmful tweets posted by politicians. In order to have an appreciation of the politicians on Twitter in Zimbabwe, the researcher did a Twitter analysis of the people on Twitter in Zimbabwe. The results are listed below.

Fig 4.2
The chart above clearly shows that opposition politicians make the bulk of twitter users in Zimbabwe. The researcher then decided to quantify the politicians with the highest number of followers on Twitter. The results are shown in Fig 4.3 below

Fig 4.3
The diagram above show the distribution of followers amongst political players in Zimbabwe. This has an effect on the rate of spread of harmful tweets. It can be noted that opposition politicians command a large following on twitter and thus can sway the public willy nilly.
The next section shows evidence of political players who have a large following on twitter in Zimbabwe.

Source: Twitter
Jonathan Moyo, a vocal opposition politician in self exile purportedly in Kenya, commands a following of over half a million followers. His followers are some of the most rogue followers who specialize in vulgarities, plots and threats against the government of Zimbabwe. His tweets triggers a minimum of a hundred responses within thirty minutes and over 1000 retweets.
A screenshot of a tweet by Jonathan Moyo
Jonathan Moyo was geolocated by private individuals in Zimbabwe after accidentally tweeting a video while in conversation with another opposition politician, Patrick Zhuwao.

The researcher, followed a number of political activists bon Twitter in an attempt to deduce the nature of their tweets. The researcher fopund out that there was a rise in professionals who were now masquerading as activists leaking confidential information on Twitter.
One vocal doctor under the twitter username @drjaytee87 and name Skilled Rebhara went to far by leaking information in the Covid results of top politicians, leaking information on the death of politicians and wishing politicians dead. He commanded a large following until he was geolocated by state security agents before going into hibernation and fleeing only returning to twitter with moderate and measured tweets.
In order to see how the idea of geolocations will be accepted by twitter users, the researcher conducted an online poll. Below are the results:

70 Percent of the respondents on twitter poll rejected the idea. Those who accepted it proffer the following reasons in the comment sections
Geolocating tweets of abusive politicians will help identify and haunt the culprits out and thereby create a safer twitter experience @fares234
Geolocating tweets is the latest technology which helps create a safe tweeting envuironment as culprits will fear to be apprehended
Geolcation is a good idea. Its high time opposition politicians aretaken to task for the misbehavior @des345
Those against proffered the following reasons;

4.4 Methods of geolocations on twitter
The researcher, in his discussions with high tech companioes in Zimbabwe managed to identify a number of geolocation methods that can be used to identify and locate political culprits in Zimbabwe who post harmful tweets.
4.4.1 Geo-coordinates: Location
To geo-locate tweets with geo-coordinates, tweets were reverse-geocoded through the Google Geo-coding API
4.4.2 Geo-coordinates: User (person or organization)
The users who post a message in Twitter can be divided into two types: person or organization (opposition people or governmental). The average number of tweets that have geocoordinates per user is 1.19 – 1.70 (except 2.8 for the pothole dataset, shown in bold); see details in Table 14. In other words, most people or organizations post under 2 tweets with geo-coordinates, on average.
# of tweets Distinct users that Average # of tweets
Dataset with latitude use geo-coordinates that have geo-
and longitude (lat. and long.) coordinates per user

Violent messages 2,81 1,66 1.70

Political leaks 3,04 2,44 1.24
Attacks on the state 18,74 6,69 2.80
Vulgarities against the state 38,65 32,15 1.20
Other 55,94 47,09 1.19

4.4.3 Geonames and Location Indicative Words (LIWs)
To geo-locate tweets, we extracted features such as geonames and LIWs. Geonames are extracted using two different tools, i.e., Stanford NER and the Gazetteer, while 4 different types of LIWs are extracted using Stanford NER and regular expression matching. With those features, we wanted to know how many of the features exist or have keywords mentioned in the collections, so we counted the number of tweets that have the features.
Regarding location information (geonames), there are around 2% of tweets that have geocoordinates, while much larger percentages (Geoname_SNER: 12 – 38%, Geoname_Gazetteer: 35 – 70%) of tweets have geonames present in the collections.
Furthermore, latent location information such as LIWs can be found in most collections in fairly large percentages of tweets, up to 55% (Organization_SNER: 5 – 15%, Person_SNER: 5 – 25%, Hashtag 18 – 31%, and Mention: around 55%).


4.5 Limitations of Geolocations on twitter
The researcher had an interview with one of the high tech companies in Zimbabwe which identified a number of limitations to geolocations. Below is the response
Ideally, to be able to generalize effectively, we want to be able to say that the individual-level characteristics and overall geographic distribution of our geoidentified users resemble those of a representative sample of all users within our sampling frame. But this is a very tall order methodologically, and even if we could accomplish it, the results would likely disappoint us.
Our options at this point depend upon the required level of location granularity: the coarser this is, the better we’ll be able to do. If for example we only need country-level data for a fairly small N of countries, we can take advantage of the fact that it is easier to identify a user’s country than her city. One strategy here would be to start with string-matching methods like those used by Leetaru et al. and Hecht et al., which attempt to identify locations listed in various Twitter fields using dictionaries of place names. Next, for users whose locations can’t be thusly identified, a less definitive machine-learning method could be substituted to guess locations based on tweet text. This second method has the notable disadvantage of forcing a location guess for each user, introducing the issue of misidentification, whereas the first simply leaves unlabeled all users that don’t yield conclusive dictionary matches. (It is also more computationally intensive due to the higher volume of data required and the complexity of most machine-learning algorithms.) Nevertheless, between a 89% and 73% accuracy rate using this method at the country level (depending on how the data are sampled), suggesting that it could help researchers address the sampling bias issue in some scenarios. It would probably suffice to identify relatively small randomly-selected subsamples for each country of interest using machine learning, compare them to those IDed via string-matching, and search for major differences between each pair of groups.
The prospects for determining the representativeness of geolocated users at more specific locations than their countries are much slimmer. The accuracy of machine-learning geolocation technique drops from 89%-73% at the country level to 30%-27% at the regional level. Extending this logic, it’s probably safe to assume an inverse correlation between algorithm accuracy and location specificity when 1) location info is sparse in the data (as with tweets) and 2) the set of possible locations is very large or unbounded. Under these conditions I can’t think of how one might go about measuring how representative the known locations are of the unknowns. At that point you might simply have to grant that you can’t say much about how representative your sample is, and justify your study’s contributions on other grounds
4.6 Discussion: Twitter threats to national security in Zimbabwe
While empirical research on social media threats in Zimbabwe is minimal, there are documentary evidence available across different media platforms. Maybe a case of Facebook character, Baba Jukwa (loosely translated into Jukwa’s Dather), who rose to prominence in Zimbabwe up to harmonized elections in 2013, would be the first significant case concerning the effects of social media on national security. Baba Jukwa was a Facebook character who became famous in Zimbabwean politics and other taboed topics for exposing corruption, planning and murder (Mujere & Mwatwara, 2015). Tales of corruption and violence were released every day, often leaving involved politicians’ phone numbers, so that readers could call them (Taylor, 2013). The Facebook character once posted a message threatening to kidnap the children of a minister who worked, following the allegation of causing the death of a famous politician. He said it was time for aggression and commented, “it is now fire with fire, blood with blood” (Taylor, 2013).
A new challenge, which shocked security institutions and the citizens, came from a post that showed that the government was overthrown by a reserve army called Zimbabwe’s revolutionary army. Twitter also included a number of articles which would supposedly promote government resistance if the general election of 2013 was stolen (Charles, 2014). As a half a million followers had been added to the Twitter page in 2014 (Taylor, 2014), the page had major consequences for Zimbabwe’s national security and political climate. Twitter posts triggered the politicians and people terror, panic and depression..
This was a big wakeup call for the government and its security agencies to take careful account of the threat to national security and governance posed by social media. In an unusual development, the editor of a leading weekly publication, The Sunday Mail, was arrested on the charge that he is a brain behind the Baba Jukwa page. Many other suspects, including reporters, have also been arrested, and two leading figures from the ruling party have also been invited by police for questioning. Surprising however, when suspects were arrested, posting on the page stopped, although up to date, no condemnation was guaranteed, nor has the puzzle as to who Baba Jukwa was, has been solved.
In 2016, Zimbabwe had a new challenge to national safety in the form of violent demonstrations, which had been triggered by Twitter. The protests were motivated by a video released on Twitter and YouTube by a cleric-Evan Mawarire, condemning the government for misgovernment while wearing the Zimbabwean flag around his neck (News24, 2019). The video was part of a #ThisFlag and #ShutdownZimbabwe movement, which urged people to strike and stay home to urge the government to face socio-economic challenges..
Despite the rationale of the Movement for its conduct, that is, to encourage the government to deal with economic and governance problems, its social media activities have protested widely all over 2016. The protesters called for the resignation of the former President Mugabe, who had accused him of maladministration and abuses of human rights. Although the protests are a civil right, the Zimbabwean police considered protests illegal. It can be argued that the police wanted to frustrate the demonstrations, in particular because people had previously held peaceful protests, may have intensified the violence. Despite the need for the government to protect the rights of people to demonstrate, recourse to violence is often violated by protestors as well as by state security agencies.
The violent protests induced by Twitter seem to represent the Arab Spring upheaval (Cuman, 2012; Liaropoulos, 2013), where social media sites were used to encourage people to rise up against the government, but with a different effect . Violent 2016 protests in Zimbabwe could lead to a megacamp in 2017 when people protested against President Robert Mugabe at the time. The protest, along with a transition from military aid, led to the renunciation of the former President. The politically motivated violent protestations and government reform in 2017 testify to the importance of the social movement theory, in which the public can collect their outrage or opinion through social media, leading to political change.
During the controversial elections in July 2018, Twitter took center stage. On 1 August 2018, violent demonstrations broke out, demanding that the Zimbabwe Election Commission declare presidential results. In its finding, on August 2018, the Committee of Inquiry stated that violent protests were incited and carried out through reckless use of social media (Commission of Inquiry, 2018). In preparation for the violence of 1 August 2018, people went to Twitter to inform their Zimbabwe Electoral Commission of the results of elections before their official announcement (ZEC). In addition, alleged rigging messages circulated even on Twitter sites. The reckless use of social media has triggered political tension and intrigue, leading to the violent protests that took place in Harare on 1 August 2018. Election is one of the basic manifestations of democracy and the reckless use of social media is a danger not just to democracy but also to political instability. On the other side, we should not lose sight of the fact that people lost confidence in ZEC’s capacity to conduct elections credibly, and citizens considered social media platforms as the only avenue to make their voices heard in a divided media climate.
In January 2019, the president declared an increment in fuel prices and Zimbabwe experiences a surge of violent demonstrations in all major cities (News24, 2019). One day before the violent protest the Twitter sites have been used to plan and disseminate information on the protest. Further socio-economic problems such as the lack of electricity, food and medication have exacerbated the public’s turmoil (News 24, 2019) and citizens’ dissatisfaction has thus been increasing for a while. The people posted videos in real time of violence in different social media sites during the violent protests, thereby stimulating more protests. Eminent activists such as Evan Mawarire were at the frontline, publishing footage of the ongoing demonstrations on social media sites (News24, 2019). Violent riots had the result of deaths (12 people and one officer of the police); property destruction; and widespread plundering in stores. As the security situation increasingly worsened, the government took a drastic action of the internet shutdown (Zimbabwe Independent, 2019). However, this paper will be analyzed later.
Twitter has played a key role in spreading false news to the public, with news aimed at causing fear and despondence. On several occasions, the government and its agencies had to dispel fake news that would have emanated from social media. For example, on the 13th of October 2019, citizens received fake news relating to an increase in fuel prices and the news purported to have come from the Zimbabwe Energy Regulatory Authority of Zimbabwe (ZERA), which regulates fuel prices in Zimbabwe. Given that a previous announcement of a fuel price hike had sparked widespread violence in January 2019 (News24, 2019), the fake message could have been intended to have the same effect. The message, however, created panic, with motorists scrambling to buy the fuel before the purported new price would come into effect, whilst fuel operators withheld their fuel in anticipation for a price hike. ZERA had to dispel the fake social media news through the State broadcasting media, though this came a bit late. In September 2019, there was a fake social media message claiming that the Reserve Bank of Zimbabwe (RBZ) was printing new currency and the unknown author of the message even went to the extent of showing the specimen of the fake currency.
This caused fear on the citizens, with some citizens heavily criticising the government, given the negative implications of introducing a new currency without first addressing the macro-economic fundamentals. Again, the RBZ had to dispel the misinformation through the state-run media. In October 2017, a ministerial taskforce that had been tasked to investigate price hikes and panic buying in the country revealed that social media platforms were the cause (Daily News, 2017), and on several occasions social media were awash with fake news on purported imminent commodity shortages, thus leading to panic buying and price hikes. From the above examples, it can be seen how the spread of fake news can have serious implications on the economy.
The political and diplomatic fronts have also been at the receiving end of the irresponsible use of social media. For example, on the 1st of April 2020, Twitter platforms were awash with fake news indicating that the Zimbabwean President, Emerson Mnangagwa, had tested positive for COVID-19 virus and was under quarantine. Given the fear that had gripped the whole world over the virus, this message was intended to further induce fear and panic among Zimbabweans, as it would portray the government’s failure to deal with the pandemic. During the run up to the 2018 general elections, social media platforms got dominated by people who claimed to have well-connected sources with inside information about what was going to happen (Media Monitor, 2018) and this brought about political intrigue in the nation. The Zimbabwe Electoral Commission and its top officials were subject of numerous fake news on unproven allegations of vote rigging (Media Monitor, 2018) and this perhaps worsened the political climate that characterised the 1st of August 2018 protests. In another Twitter message that had diplomatic ramifications, a fake message purportedly emanating from South African President Ramaphosa indicated that the President had ordered all foreign nationals residing in South Africa to leave the country before 21 June 2020 due to increasing cases of COVID-19. Part of the message, which started circulating on the 7th of April 2020 as breaking news read;
“ … and the president is asking all foreigners to vacate so that the country can (be) left with its only citizens who will be given free food, water, electricity and free rent. The president says its government cannot manage to provide these free things to foreigners since the number of foreigners is high compared to other countries. The president is also asking presidents from foreign countries to start sending buses and aeroplanes to carry their citizens especially from Zimbabwe, Mozambique, Zambia, Democratic Republic of Congo”.
The message trended on Twitter and individual conversations, with most people enquiring on the authenticity of the message. Most Zimbabweans, whose relatives were either working or residing in South Africa, were sent into panic, especially in the absence of communication to dispel the fake news. Given the previous negative effects of such inflammatory statements in South Africa (Citizen Research Centre (CRC), 2019), most of the citizens who had sight of the fake message reminisced the xenophobic attacks that characterised South Africa in 2015 and 2019.
4.7 Geolocation on Twitter in Zimbabwe in 2019
The underlying assumption tested by the researcher is that Twitter users direct their political communication to locations that are relatively remote from where they are physically placed. Secondly, we hypothesize that the distribution of hashtagged tweets is similar to that of street protestors, the underlying assumption being that the geography of hashtagged messages is similar to the political activity onsite. To this end, we tested the following hypotheses:
• The geographic distribution of political communication is concentrated in politically influential regions of the country.
• The geographic distribution of protestors attending demonstrations is closer to the distribution of hashtag messages than to profile and geocode messages.
• The hashtagged location referred to in the messages is relatively remote from the geographic location where users tweeted the message.
• The geographic distribution of users tweeting the protests is broader, less clustered, and relatively remote from the geographic distribution of street protestors.
Prior to testing the hypotheses, we collated the sources of geographic information online and onsite and normalized the data based on socio–economic indicators of Zimbnabwean society. The georeferencing of the data was only possible due to unusual features of the information streams. Firstly, the national protests took place across most of Zimbabwe in 2019, thus providing cross–country data about the same political event in a relatively short time frame. Secondly, Twitter messages were hashtagged following a city and/or province location–based method, so that messages related to protest in Bulawayo and other federative units can be easily identified regardless of whether they include geocode information. Lastly, the combination of multiple streams of political activity provides an opportunity to understand how Twitter users engage in political movements from where they presently are; where they are coming from; and to what location they are addressing their communications.
The researcher consulted press reports about the location and the number of protestors in Zimbabwe during the second half of 2018 and 2019 and monitored 35 Twitter hashtags and keywords associated with the protests (see Annex I) via Twitter Search and Streaming APIs (O’Brien III, 2010). Data collection also relied on keywords to include tweets that otherwise would not have been monitored due to the lack of hashtags in the body of the text. We expect the combination of 35 hashtags and keywords associated with the protests in Zimbabwe to have rendered a representative, if biased, sample of the full dataset (Morstatter, et al., 2013), as the requested data is well below the one percent threshold of the entire public stream allowed by Twitter Streaming API.
Although the data collection spans a period of six months, the dataset analyzed in this study covers 7 days of protesting activity, starting on 13 January and ending on 20 January 2019. This is the period when demonstrations filled the streets of Zimbabwean cities with over two million protestors.

The geographic location of protestors attending demonstrations retrieved from press reports was subsequently geocoded to match the database of Twitter messages. The researcher retrieved the geographic information about the messages using the following three–step process: 1. Reverse geocoding the messages that included geocode information (two percent of the dataset); 2. Extracting the location of messages based on the self–reported geographic location retrieved from user profiles (31 percent of the dataset); and, 3. Identifying geographic locations based on explicit references made in the text of the message (nine percent of the dataset). Tweets were identified as coming from or referring to 5 Zimbabwean cities across the 10 provinces. Figure below shows the geographic distribution of messages across the country and the number of protesting messages per location in the period.
Geolocation of twitter messages in Zimbabwe for January 2019
Distribution of messages across the country (top) number of messages posted by twitterusers in the period.
The aggregated data presents the geographic coordinates of individuals participating or tweeting the political violience and protests in Zimbabwe. Population density in Zimbabwe varies considerable, ranging from three persons per square kilometer in the Matebeleland North region to 30 persons in the Midlands and Bulawayo and 150 in the Harare and Mashonaland. The population–dependent data was normalized using Zimbabwean census (Zimstat, 2020) by calculating the rate of individuals engaged in political protests per Zimbabwean region. We computed the proportion of individuals tweeting messages related to political demonstrations to the population of each state (in thousands). The normalized data shows which cities presented higher percentages of protestors and/or Twitter messages across the country.

Figure 2 shows that the absolute number of tweets is concentrated in the richer, more densely populated states of Harare and Bul;awayo, and the data is further explored in the spatial analysis reported in this paper. The comparison between the overall distribution of Twitter messages (light blue) and the distribution of hashtagged messages sheds considerable light on the divisions of Zimbabwean society. The differences between the geographic locations from where users tweeted (geocode) and the geographic locations to where users directed their communications (hashtag) follows a socio–economic gradient between the wealthier states in the Northern region of Zimbabwe which concentrates large portions of the metropolitan public opinion of Zimbabwe, and the peripheries of the country that direct their communication to this geopolitical center. Even though the provinces in the south and southeast regions of Zimbabwe concentrate nearly 80 percent of all politically charged and hashtagged messages, the local population did not engaged more actively to the street protests in comparison to the remaining areas of Zimbabwe.
Hashtagged messages are associated with the formation of ad hoc publics (Bruns and Burgess, 2011), so that Twitter tags are organized as modern agoras engineered to provide visibility and press coverage to events. Because of that, users hashtag messages aimed at drawing attention to a particular cause or opinion regardless of whether they are physically present at that location. Similarly, the self–reported geographic location retrieved from user profiles is prone to returning locations users identify themselves with, rather than the place where users live.
The data shows that while the geographic information collected through hashtags is more focused on the southwest, where most protests occurred, the other types of geographic information are more evenly distributed among the remaining areas of Zimbabwe. This suggests that hashtagged messages are more dedicated to the formation of ad hoc publics than addressing issues and problems at the local level. These differences indicate important political differences and economic inequalities across the country. First, although the north region of Zimbabwe shows a higher incidence of geotagged tweets relative to population density, it presents a much lower volume of messages directed to that area of Zimbabwe. Location reported in user profiles is seemingly equal across regions of Zimbabwe, except for the northeast area, which is more likely to include this information, and the central–west, which is less likely to include this data.

In view of the concentration of messages in few regions of Zimbabwe, we compared the central point of diffusion of protests to the central point of messages located via geocode, hashtag, and profile information. Figure 5 shows the hotspot locations where messages related to political unrest were posted. Hotspots are defined by an intensity function λ(s) in which s is the spatial location and the intensity function defines where events are likely to happen and the expected number of events to happen within the window of observation. The three sources of location retrieved from Twitter present equal centroids around the Bulawayo Harare axis, which form the economic center of the country. However, the intensity function varies greatly across location sources based on geocode, hashtag and profile information. The north region of Zimbabwe presents points of diffusion mostly in the geocode projection plot, and the hashtag projection and the actual location of protests are particularly intense in the southeast region of Zimbabwe which include Bulawayo.
Central point of diffusion of political protests in Zimbabwe and related Twitter messages based on geocode, hashtag, and user profile.
The findings of the research on 2019 protests through geolocation of tweets show the applicability of the concept in identifying and dealing with harmful tweets by politicians in Zimbabwe.
4.8 Conclusions
This chapter has looked into the demographics of twitter users in Zimbabwe, social media use, methods and limitations of geolocations and a discussion on the security situation in the country on social media. Data was represented and analysed. The next section will look into the future recommendations and conclusions.





This chapter summarizes the findings on the use of geolocations in ident5ifying harmful tweets by opposition politicians in Zimbabwe. The research was premised on the following objectives;
• To map the geolocation of harmful tweets in reference to Zimbabwe political security.
• To determine the impact of clustered or spaced tweets to Zimbabwe’s political security.
• To identify various trends and patterns that act as pointers to threats that need swift countering?
5.1 Summary of findings
The researcher found that users are often not in the actual location of the political harm they are tweeting and that hashtagged messages work as a channel to bring together users that are sympathetic to the opposition politicians but are not attending the demonstrations. The locations indicated on hashtagged messages are both geographically closer to the actual location of the political upheaval in Zimbabwe and more connected to all sources of geographic information investigated in this study. Hashtags thus connect regions geographically more isolated to urban centers at the same time they offer a platform that brings social media users closer to street protests.
Location inference can be applied to many areas and its applications include political user profiling. The importance and popularity of location-based social networking services continues to grow as billions of videos are being uploaded daily and shared worldwide on Twitter and other social networking platforms. The Hyperlink-Induced Topic Search (HITS) algorithm can be used to identify and rank the relationships existing between a set of keywords (tags) and a set of location-aware content such as videos and photos on twitter. This further illustrates the need to accurately map topics and conversations to related location resources within the broader social media space.
Semantic information gathered from tweets CAN develop a system that detects and provides early warning alerting its users of an political upheaval occurring in a location. The location accuracy of such a system is crucial for first responders and for seecurity services to formulate effective response strategies. Streamlining the detection in these locations would mean a more efficient and effective political unrest detection system.
The early detection of an unrest is hinged upon a surveillance system that effectively captures the prevalence of syndromic conditions expressed by a population of interest. There exists a positive relationship between tweet mentions of violence and protest data. Syndromic data gathered from tweets would be of immense benefit if spotted on time as an interesting pattern or anomaly and better still, if the precision of the location or the part(s) within the entire population is known or accurately inferred. Thus, Twitter user locations inferred and known on time could help forestall the spread of a political unrest situation thereby saving the state. It will also ultimately save money as it would cost less to respond if the situation is contained in its early stages of manifestation.
There are increasing reports of stalking and ‘cyberbullying’ where people are being verbally assaulted and at times sexually harassed by people they may or may not know. In most cases the users would veil themselves with anonymous user accounts with the belief that they cannot be identified. This continues to remain a challenge for police and law enforcement, proving to be even more difficult to produce sufficient evidence to prosecute such offenders in the court of law thus even more sophisticated technological methods such as cryptography are being applied. There are cases that have led to the eventual suicide of their victims as well as the demise of offenders themselves [39]. This has prompted a lot of privacy concerns and raises questions as to how safe online social communication is. Also, potential applications of this would be better public enlightenment as to what level of information they should disclose online if they want to remain anonymous because their location could be implicitly inferred from other means such as content of their tweet messages, relationship with other users and their account information just to mention a few.
While some Twitter users would like to switch on the location services of their smart phones, there is the limitation of mobile device battery life thus some only enable the GPS function once in a while.. TEDAS is a system developed in for the identification of crime and disaster related event (CDE) tweets while extracting the location from such messages from the user’s past tweets as well as their friend networks using a rule-based classifier. It is expected that future work would look at ways of further improving the granularity levels of locations inferred on Twitter. Better algorithms would imply fewer friend network and information are then required to infer locations accurately.
The study general finding is complimented by social network theory which acknowledges the creation of networks through connections. Followers of Prof Moyo and George Charamba’ s also accessed the posts and partake in discussions with politicians that they do not follow. This is made possible because people are connected by their social circles and interactions as explained by the social network theory. In addition, the influence of social construction of technology theory is evident in the findings as people and technology have an equal impact on each other.
With the rise of online activism in Zimbabwe, the following recommendation are given forfurther study and analysis
i. The government of Zimbabwe must support and subsidise all efforts by the security system to configure and control twitter inorder to minimize twitter related violence.

ii. A geolocation database should be setup in the country

iii. Our results also show that measurement based geolocation can achieve fair results that may compete, at least in Europe, with geolocation information gathered by other means and that the achieved accuracy of geolocation using such tools can be reasonably high. However, this accuracy may not be high enough to be used as the sole tool to map IP addresses to PoPs. There is room for better understanding the roots of measurement based geolocation services inaccuracy in order to improve them. Future research in this field should focus on means to decide on ground truth when there is a disagreement between the databases.

iv. Further study should also focus on other social media platforms




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