Dissertation/Thesis Abstract

Understanding Social Movements through Simulations of Anger Contagion in Social Media
by Bacaksizlar, Nazmiye Gizem, Ph.D., The University of North Carolina at Charlotte, 2019, 103; 13805848
Abstract (Summary)

This dissertation investigates emotional contagion in social movements within social media platforms, such as Twitter. The main research question is: How does a protest behavior spread in social networks? The following sub-questions are: (a) What is the dynamic behind the anger contagion in online social networks? (b) What are the key variables for ensuring emotional spread? We gained access to Twitter data sets on protests in Charlotte, NC (2016) and Charlottesville, VA (2017). Although these two protests differ in their triggering points, they have similarities in their macro behaviors during the peak protest times. To understand the influence of anger spread among users, we extracted user mention networks from the data sets. Most of the mentioned users are influential ones, who have a significant number of followers. This shows that influential users occur as the highest in-degree nodes in the core of the networks, and a change in these nodes affects all connected public users/nodes. Then, we examined modularity measures quite high within users’ own communities. After implementing the networks, we ran experiments on the anger spread according to various theories with two main assumptions: (1) Anger is the triggering emotion for protests and (2) Twitter mentions affect distribution of influence in social networks. We found that user connections with directed links are essential for the spread of influence and anger; i.e., the angriest users are the most isolated ones with less number of followers, which signifies their low impact level in the network.

Indexing (document details)
Advisor: Hadzikadic, Mirsad
Commitee: Maestas, Cherie, Ras, Zbigniew W., Shaikh, Samira
School: The University of North Carolina at Charlotte
Department: Information Technology
School Location: United States -- North Carolina
Source: DAI-B 80/07(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Information Technology, Sociology, Web Studies, Systems science
Keywords: Agent-based modeling, Computational social science, Emotion contagion, Natural language processing, Social media, Social movements
Publication Number: 13805848
ISBN: 9780438892415
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