Understanding online protests unveiling strategies collective narratives and harmful behaviors

Abstract

Protests (or movements) are a form of collective sociopolitical action in which mem- bers with similar beliefs express their objections to a cause or situation. Often, a heated debate during protests on social media, such as Twitter, may lead to divided users and divergent discourse. On the bright side, studying divergent discourse on contentious topics can help infer the collective perceptions of people in terms of their collective narratives. On the dark side, narratives shared during protests may become susceptible to various harmful influence operations, disrupting society s peaceful fabric. This thesis aims to understand digital strategies to organize protests, identify collective narratives shared during protests, and identify harmful behaviors with potential online and offline consequences. We focus on hate speech and coordinated inauthentic behavior as prox- ies for harmful conduct during online protests. We divide the thesis into four parts: (i) Understanding strategies used for conducting online protests, (ii) Detecting and analyz- ing collective narratives shared during protests, (iii) Detecting and analyzing opposing stances during the protest, inclusive of authentic and inauthentic actors, (iv) Detecting and analyzing harmful behavior during protest. To focus on the strategies used for conducting protests on social media, we examine the protest over the cause of the death of Sushant Singh Rajput (#SSR) 1 on Twitter. Study of shared hashtags and retweets during #SSR protests reveals a combination of centralized and decentralized information aggregation strategies in retweet networks, suggesting a mix of self-motivated individuals and organized entities. Next, we pro- pose an unsupervised clustering-based framework to focus on the collective narratives shared during protests. Our findings suggest clusters of call-to-action and on-ground activities across protests under study. newline