This thesis contains no text, graphics or tables copied and pasted from the Internet, unless specifically acknowledged and the source is detailed in the thesis and References sections. I thank my heavenly Father for the life you gave me and for the gift of thought.
INTRODUCTION
Based on this context, the study aimed to discover how the #FeesMustFall social movement was represented on Twitter, as well as to analyze the communication behaviors of the members of this community. Therefore, Hauser's (1999) public sphere of rhetoric became a key part of the methodological framework because it guided the analysis of interactions drawn from the #FeesMustFall community.
LITERATURE REVIEW
Data information is the ability that networked platforms have to quantify aspects of the world (Mayer-Schoenberger and Kenneth Cukier, 2013). This is further reinforced by Koopman (2004), whose work is based on the evolution of the German radical right in the 1990s. Based on the various descriptions of the 'MustFall' movements the following can be concluded by Bruns and Highfield.
Habermas (1964) places great emphasis on the power of the mass media in writings in the public sphere.
METHODOLOGY
To accomplish this task a coding framework informed by the features of the Hauserian public sphere was developed. The second phase used the network analysis tool Gephi to analyze the network structure of the community and identify who the most influential users were and the content they shared. Qualitative content analysis systematically describes the meaning of qualitative data "by assigning successive pieces of material to the categories of a coding frame" (Schreier.
Furthermore, the method allows for flexibility because the coding framework takes into account the context of the data and the focus of analysis provides detailed descriptions of the material. Additionally, the data set was split by week and some weeks within the data set were shown as the 'heavy' weeks of the data set. When coding the tweets, an a priori decision was made to code members according to their profile within the community.
PB3 If the conversations showed evidence of opposition to the views of the general population of the #FeesMustFall community. The fourth category sought to determine how plausible the #FeesMustFall network discourse was. Social network analysis begins with the creation of sociograms, which provide a graphical representation of the relationship between nodes (users) and edges (conversations).
DATA ANALYSIS
As discussed in the previous chapter, the data analyzed comes from a specific moment in the movement, where community members began to question the movement's ideals following a series of violent disputes and divisive rhetoric. However, before this could be analyzed in detail, it was important to determine who the active members of the community were. As shown in Figure 1, it was found that university students and the general public made up almost half of the population in the #FeesMustFall community.
As we will see, this group was instrumental in bringing Group A information out of the darkness and into a greater light on Twitter and in the broader public sphere.
MEMBER IDENTITIES
This is due to the significant drop in community membership from September 31 to October 14, which represents a decrease in the use of the. This was due to community members crossing over with members outside their immediate network, and heavy use of the hashtag #FeesMustFall. This was due to community members abandoning the #FeesMustFall hashtag and often opting for another one.
After examining the statistics of the network structure, analysis moved to consider how information is distributed within the community. One of the main objectives of this study was to look at the social activity within the. This made the network structure grow, especially in the first two weeks of the month.
This resulted in critics of the movement such as @SihleDLK rising in profile in the network. Community members used framing techniques to make content more relatable to other users. But before looking at which members of the community gained the most influence, it was important to unpack the themes in the most popular tweets.
Hauser Codes of Analysis
As discussed in Chapter 2, the norms of the rhetorical public sphere are: permeable boundaries, activity, contextualized language, credible appearance, and tolerance, and as highlighted in Chapter 3, they are used to analyze the dialogue that surrounded it. Looking at Figure 19, one might believe that the most frequently represented codes may be the most important codes of the data set. Therefore, each category should not be seen as more important than the other, but rather indicative of the changing contexts highlighted in the conversations.
According to the dataset, reference to social issues was high in both weeks, resulting in 5% of the dataset talking about issues other than #FeesMustFall. To contextualize the movement to suit potential members, the society could not deal with issues that were limited to issues of fees alone. For example, the most popular subcode in week 1 was PB2, which referred to general social issues.
PB1 If the conversations were about other hashtag movements that were popular at the time. PB3 If conversations showed evidence of opposition to community views #FeesMustFall. PB4 If the conversations received support and/or recognition from other groups or social movements in the Twittersphere.
PERMEABLE BOUNDARIES
Despite the criticism in the previous category, permeable boundaries, the majority of tweets in the dataset showed support for the movement. As shown in Figure 26, the member continues to highlight the government's shortcomings. A8 talks about the effect of the movement on the national economy. A9 conversations against caused by students.
This further highlighted the ambiguity of some of the arguments put forward by the community. Noteworthy, however, is the increase in the A7 subcode in week 2, as seen in Figure 31, which could be the result of growing criticism of the movement's ideals in the community. Such tweets caused divisions within the community because there were now differing views on the true ideals of the movement.
As can be seen from Figure 54, the majority of users agreed with this sentiment. This is further emphasized by some of the tweets that were distributed within the network. As can be seen in Figure 38, reports of the incident claim that Father Pugin was shot by the police despite being unarmed.
UNIVERSITIES BY MENTION
FINDINGS AND CONCLUSION
For example, some leaders of the movement were being arrested, and so a #BringBackOurCadres story was trending. This is why it was necessary to separate the different members of the community according to their social position. For example, @WitsSRC, rose to the fore as a hub of network information, due to the quality of content found on their site.
The rhetoric used to describe the movement offered an interesting insight into how the community was able to develop an identity for the topic of fees. These spinoff hashtags described certain aspects of the troubled community and later gained support from members of the #FeesMustFall community. However, from a communication point of view, this could serve as an example of a community's response to the stimuli around them.
Further inspection of the tweets also revealed an element of 'whistleblowing' by some members of the community. Some publications framed the altercation as violent, tarnishing the movement, even though most of society advocated that they were the victims. Using the norms of the rhetorical public sphere as the main tool for textual analysis, the voices of the members of the #FeesMustFall community were heard.
The Rise of the Network Society, With a New Preface: The Information Age: Economy, Society, and Culture Volume I. Beyond Difference: Using Blank Signifiers as Organizing Devices in the #Occupy Movement. Paper presented at the seminar Material Participation: Technology, Environment and the Everyday Public, University of Milan.
Special section: Transnational public sphere: Transnationalization of the public sphere: on the legitimacy and effectiveness of public opinion in a post-Westphalian world. In Games, Learning and Society: Learning and Meaning in the Digital Age, Cambridge University Press pp. Sharing News on Facebook: An Analysis of the Students of the University of KwaZulu-Natal, Pietermaritzburg Campus (Unpublished Honors Project) University of KwaZulu-Natal, Pietermaritzburg, South Africa.
Differences in the mechanics of information dissemination across topics: idioms, political hashtags, and complex twittering.
APPENDICES
Everything that exists in this country, the culture, they decide how it works where it works and when it works. We leave you with those words, so that when you think now, you won't think based on other assumptions about color. RT @MbuyiseniNdlozi: Whatever happens remember this: Unity in struggle is the only guarantee of victory.
RT @Julius_S_Malema: The time for free education is now, police brutality will never succeed in suppressing a noble course #FeesMustFall. RT @Julius_S_Malema: We all know who sold our parents dreams in 1994 promising free education, that should be a goal. RT @Adamitv: #SJM invites #Student #Leaders of #FeesMustFall to a meeting to discuss solutions for #FreeEducation for the Poor.
RT @Adamitv: The demand by @witsfmf #FeesMustFall students that "power" meet them publicly shows arrogance or ignorance of student leadership.
