Document Type : Original Article

Authors

1 Department of Sociology, Faculty of Social Sciences, Tehran University, Tehran, Iran

2 Ph. D Student, Sociology of Development, Faculty of Social Sciences, Tehran University, Tehran, Iran

Abstract

In this research, through identifying the components of what is called “Iranian Twitter”, we tried to identify and evaluate the patterns of how Iranian Twitter users are affected by the political attitudes of the Iranian Twitter Influencers. For this purpose, Influencers and Followers including 917,318 Iranian users of Twitter were categorized based on their political attitudes; then, patterns of how Followers were affected by Influencers were identified and evaluated for various political attitudes. To categorize Influencers and Followers, we used data mining techniques, and to analyze network data, we applied Gephi software. The results showed that although none of the political attitudes in Iranian Twitter have significant superiority to others, a significant proportion of users who favored a political attitude, displayed little tendency to be exposed to different political messages.     

Keywords

Main Subjects

Barberá, P, Jost, J, Nagler, J, Tucker, J, Bonneau, R. (2015). Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber?, Psychol. Sci., 26:1-12.
Bauman, Z. (2016). Zygmunt Bauman: Social media are a trap, Retrieved from ELPAIS:https://english.elpais.com/elpais/2016/01/19/inenglish/1453208692_424660.html.
Blockspring. (2018). Reports, Retrieved from Blockspring: https://www .blockspring. com/.
Castells, M. (2012). Networks of outrage and hope: Social movements in the Internet age, Cambridge: Polity.
Colleoni, E, Rozza, A, Arvidsson, A. (2014). Echo Chamber or Public Sphere? Predicting Political Orientation and Measuring Political Homophily in Twitter Using Big Data. J. Communicat., 64:317-332.
Dubois, E, Blank, G. (2018). The echo chamber is overstated: the moderating effect of political interest and diverse media. Information, Communicat. Soc., 21:729-745.
Faina, J. (2012). Twitter and the New Publicity, Institute General Semant., 69(1): 55-71.
Gephi. (2018). About, Retrieved from Gephi: https://gephi.org/about/.
Heymann, S. (2015). PageRank, Retrieved from GitHub: https://github.com/gephi/gephi/wiki/PageRank.
Mertia, S. (2014). Theorising Identity on Twitter, Retrieved from Academia: https://www.academia.edu/5410689/Theorising_Identity_on_Twitter.
Morris, T. (2009). All a Twitter: A Personal and Professional Guide to Social Networking with Twitter, Indianapolis: Que.
NODUS LABS. (2018). Network Visualization and Analysis with Gephi, Retrieved from NODUS LABS: https://noduslabs.com/courses/network-visualization-and-analysis-with-gephi/units/section-1-quick-introduction-to-network-analysis/page/10/?try.
OMNICORE. (2018). Twitter by the Numbers: Stats, Demographics & Fun Facts, Retrieved from OMNICORE: https://www.omnicoreagency.com/twitter-statistics/.
Pérez-Altable, L. (2016). The Arab Spring before the Arab Spring: A case study of digital activism in Tunisia, Retrieved from Researchgate:https://www.researchgate .net/publication/294548657_The_Arab_Spring_before_the_Arab_Spring_A_case_study_of_digital_activism_in_Tunisia
Statcounter. (2018). Social Media Stats Islamic Republic Of Iran, Retrieved from Statcounter: http://gs.statcounter.com/ social-media-stats/all/iran.