Abstract
Within complex societies, social communities are distinguishable based on social interactions. The interactions can be between members or communities and can range from simple conversations between family members and friends to complex interactions that represent the flow of money, information, or power. In our modern digital society, social media platforms present unique opportunities to study social networks through social network analysis (SNA). Social media platforms are usually representative of a specific user group, and Twitter, a microblogging platform, is characterised by the fast distribution of news and often provocative opinions, as well as social mobilizing, which makes it popular for political interactions. The nature of Twitter generates a valuable SNA data source for investigating political conversations and communities, and in related research, specific archetypal conversation patterns between communities were identified that allow for unique interpretations of conversations about a topic. This paper reports on a study where social network analysis (SNA) was performed on Twitter data about political events in 2021 in South Africa. The purpose was to determine which distinct conversation patterns could be detected in datasets collected, as well as what could be derived from these patterns given the South African political landscape and perceptions. The results indicate that conversations in the South African political landscape are less polarized than expected. Conversations often manifest broadcast patterns from key influencers in addition to tight crowds or community clusters. Tight crowds or community clusters indicate intense conversation across communities that exhibits diverse opinions and perspectives on a topic. The results may be of value for researchers that aim to understand social media conversations within the South African society.
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Notes
- 1.
The hashtag lists are depicted exactly as they appear in the tweets with the same capitalisations. Twitter users aims to use similar hashtag lists when the mention, reply or retweet.
References
Fu, X., Jar-Der, L., Boos, M.: Social Network Analysis: Interdisciplinary Approaches and Case Studies. CRC Press, Boca Raton (2017). https://doi.org/10.1201/9781315369594
Scott, J., Carrington, P.J. (eds.): The SAGE Handbook of Social Network Analysis. SAGE, London (2011)
Hanna, R., Rohm, A., Crittenden, V.L.: We’re all connected: the power of the social media ecosystem. Bus. Horiz. 54, 265–273 (2011). https://doi.org/10.1016/j.bushor.2011.01.007
Perrin, A.: Social media usage: 2005–2015. Pew Research Center (2015). https://www.secretintelligenceservice.org/wp-content/uploads/2016/02/PI_2015-10-08_Social-Networking-Usage-2005-2015_FINAL.pdf
Kaplan, A.M., Haenlein, M.: Users of the world, unite! The challenges and opportunities of Social Media. Bus. Horiz. 53, 59–68 (2010). https://doi.org/10.1016/j.bushor.2009.09.003
Schivinski, B., Dabrowski, D.: The effect of social media communication on consumer perceptions of brands. J. Market. Commun. 22, 189–214 (2016). https://doi.org/10.1080/13527266.2013.871323
Wellman, B. (ed.): Networks in the Global Village: Life in Contemporary Communities. Westview Press, Boulder (1999)
Khan, G.F.: Seven Layers of Social Media Analytics: Mining Business Insights from Social Media Text, Actions, Networks, Hyperlinks, Apps, Search Engine, and Location Data. CreateSpace Independent Publishing Platform, Leipzig (2015)
Tichy, N.M.: Social network analysis for organizations. Acad. Manage. Rev. 4, 507–519 (1979)
Kietzmann, J.H., Hermkens, K., McCarthy, I.P., Silvestre, B.S.: Social media? Get serious! Understanding the functional building blocks of social media. Bus. Horiz. 54, 241–251 (2011). https://doi.org/10.1016/j.bushor.2011.01.005
Green, S., Perrin, A.: Social media update 2016. Pew Research Center (2016)
Weller, K.: Trying to understand social media users and usage: the forgotten features of social media platforms. Online Inf. Rev. 40, 256–264 (2016). https://doi.org/10.1108/OIR-09-2015-0299
The Evolution of Social Media: How Did It Begin and Where Could It Go Next? https://online.maryville.edu/blog/evolution-social-media/. Accessed 07 Sept 2021
Walton, J.: Twitter vs. Facebook vs. Instagram: What’s the Difference? (2021). https://www.investopedia.com/articles/markets/100215/twitter-vs-facebook-vs-instagram-who-target-audience.asp
Adamic, L.A., Glance, N.: The Political Blogosphere and the 2004 U.S. Election: Divided They Blog. 8 (2005)
Bennett, W.L.: The personalization of politics: political identity, social media, and changing patterns of participation. Ann. Am. Acad. Polit. Soc. Sci. 644, 20–39 (2012). https://doi.org/10.1177/0002716212451428
Trottier, D.: Social Media, Politics and the State: Protests, Revolutions, Riots, Crime and Policing in the Age of Facebook, Twitter and YouTube. Routledge (2014). https://doi.org/10.4324/9781315764832
Allen, K.: Social media, riots and consequences (2021). https://issafrica.org/iss-today/social-media-riots-and-consequences
Karombo, T.: South Africa goes after social media as it cracks down on looting and protests. https://qz.com/africa/2033328/south-africa-to-monitor-social-media-as-protests-rock-the-country/. Accessed 07 Sept 2021
Makhafola, G.: #UnrestSA: Two more alleged instigators arrested, including one who ran popular Twitter account (2021). https://www.news24.com/news24/southafrica/news/unrestsa-two-more-alleged-instigators-arrested-including-one-who-ran-popular-twitter-account-20210829
Twitter. https://twitter.com/home. Accessed 20 June 2020
Kane, G.C., Alavi, M., Labianca, G. (Joe), Borgatti, S.P.: What’s different about social media networks? A framework and research agenda. MISQ. 38, 274–304 (2014). https://doi.org/10.25300/MISQ/2014/38.1.13
Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)
Borgatti, S.P., Everett, M.G.: Notions of position in social network analysis. Sociol. Methodol. 22, 1 (1992). https://doi.org/10.2307/270991
Hansen, D.L., et al.: Do You know the way to SNA? A process model for analyzing and visualizing social media data. In: International Conference on Social Informatics, p. 10. IEEE (2012)
Rainie, H., Wellman, B.: Networked: The New Social Operating System. MIT Press, Cambridge (2012)
Rodrigues, E.M., Milic-Frayling, N., Smith, M., Shneiderman, B., Hansen, D.: Group-in-a-box layout for multi-faceted analysis of communities. In: 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing, pp. 354–361. IEEE, Boston (2011). https://doi.org/10.1109/PASSAT/SocialCom.2011.139
Clauset, A., Newman, M.E.J., Moore, C.: Finding community structure in very large networks. Phys. Rev. E 70 (2004). https://doi.org/10.1103/PhysRevE.70.066111
Woma, J.: Comparisons of Community Detection Algorithms in the YouTube Network. Stanford University, Stanford (2019)
Social Media Research Foundation. https://www.smrfoundation.org/. Accessed 30 June 2020
Fay, D.: NodeXL: Network Overview, Discovery and Exploration in Excel. https://www.microsoft.com/en-us/research/project/nodexl-network-overview-discovery-and-exploration-in-excel/. Accessed 30 June 2020
Hansen, D.L., Schneiderman, B., Smith, M.A.: Analyzing Social Media Networks with NodeXL: Insights from a Connected World. Morgan Kaufmann, Burlington (2011)
Smith, M., Rainie, L., Shneiderman, B., Himelboim, I.: Conversational Archetypes: Six Conversation and Group Network Structures in Twitter. https://www.pewresearch.org/internet/2014/02/20/part-2-conversational-archetypes-six-conversation-and-group-network-structures-in-twitter/. Accessed 08 Sept 2021
Himelboim, I., Smith, M.A., Rainie, L., Shneiderman, B., Espina, C.: Classifying twitter topic-networks using social network analysis. Soc. Media Soc. 3, 205630511769154 (2017). https://doi.org/10.1177/2056305117691545
Smith, M.A., Rainie, L., Shneiderman, B., Himelboim, I.: Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. https://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/. Accessed 19 Sept 2019
Smith, M.A., Rainie, L., Shneiderman, B., Himelboim, I.: Part 2: Conversational Archetypes: Six Conversation and Group Network Structures in Twitter. https://www.pewresearch.org/internet/2014/02/20/part-2-conversational-archetypes-six-conversation-and-group-network-structures-in-twitter/. Accessed 02 Aug 2021
Ndwandwe, Z.: The myth of South African nationality. https://africasacountry.com/2020/10/the-myth-of-south-african-nationality. Accessed 01 Sept 2021
Seemela, M.: “#PutSouthAfricaFirst shouldn’t be used to hate anybody,” says Cassper. https://www.timeslive.co.za/tshisa-live/tshisa-live/2020-10-19-putsouthafricafirst-shouldnt-be-used-to-hate-anybody-says-cassper/. Accessed 01 Sept 2021
Tabane, R.: ANALYSIS | Will the governing party ride out the ‘Voetsek, ANC’ storm? https://www.news24.com/citypress/politics/analysis-will-the-governing-party-ride-out-the-voetsek-anc-storm-20200827-2. Accessed 20 Sept 2021
Lindeque, B.: #VoetsekANC has been trending for over a week now... and this response. https://www.goodthingsguy.com/opinion/voetsekanc-has-been-trending-for-over-a-week-now-and-this-response-is-pretty-funny/. Accessed 20 Sept 2021
Haffajee, F.: Covid-19 – The 150 Days report (Part 1): Fix South Africa or fix the ANC – Ramaphosa can’t do both. https://www.dailymaverick.co.za/article/2020-08-10-fix-south-africa-or-fix-the-anc-ramaphosa-cant-do-both/. Accessed 20 Sept 2021
IOL Reporter: LIVE UPDATES: #SouthAfricaIsBurning – Shock as widespread looting rages on. https://www.msn.com/en-xl/africa/other/live-updates-southafricaisburning-shock-as-widespread-looting-rages-on/ar-AAM8uI3. Accessed 20 Sept 2021
Lechman, A.: Ramaphosa’s words falls on deaf ears as looting continued in SA - Sunday World. https://sundayworld.co.za/breaking-news/ramaphosas-words-falls-on-deaf-ears-as-looting-continued-in-sa/. Accessed 20 Sept 2021
Mokoka, M.: Meet the Instigators: The Twitter accounts of the RET Forces Network that Incited Violence and Demanded Zuma’s Release. Centre for Analytics and Behavioural Change (2021)
Fruchterman, T.M.J., Reingold, E.M.: Graph drawing by force-directed placement. Softw. Pract. Exper. 21, 1129–1164 (1991). https://doi.org/10.1002/spe.4380211102
Maré, G.: Race, democracy and opposition in South African politics: as other a way as possible. Democratization 8, 85–102 (2001). https://doi.org/10.1080/714000182
Seekings, J.: The continuing salience of race: discrimination and diversity in South Africa. J. Contemp. Afr. Stud. 26, 1–25 (2008). https://doi.org/10.1080/02589000701782612
Ndlovu, N.: ‘A nation that laughs together, stays together’: deconstructing humour on twitter during the national lockdown in South Africa. In: Mpofu, S. (ed.) Digital Humour in the Covid-19 Pandemic, pp. 191–212. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-79279-4_9
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Gerber, A. (2022). The Detection of Conversation Patterns in South African Political Tweets Through Social Network Analysis. In: Jembere, E., Gerber, A.J., Viriri, S., Pillay, A. (eds) Artificial Intelligence Research. SACAIR 2021. Communications in Computer and Information Science, vol 1551. Springer, Cham. https://doi.org/10.1007/978-3-030-95070-5_2
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