The Pursuit of Being Heard: An Unsupervised Approach to Narrative Detection in Online Protest

Kumari Neha, Vibhu Agrawal, Arun Balaji Buduru, P. Kumaraguru
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Abstract

Protests and mass mobilization are scarce; however, they may lead to dramatic outcomes when they occur. Social media such as Twitter has become a center point for the organization and development of online protests worldwide. It becomes crucial to decipher various narratives shared during an online protest to understand people's perceptions. In this work, we propose an unsupervised clustering-based framework to understand the narratives present in a given online protest. Through a comparative analysis of tweet clusters in 3 protests around government policy bills, we contribute novel insights about narratives shared during an online protest. Across case studies of government policy-induced online protests in India and the United Kingdom, we found familiar mass mo-bilization narratives across protests. We found reports of on-ground activities and call-to-action for people's participation narrative clusters in all three protests under study. We also found protest-centric narratives in different protests, such as skepticism around the topic. The results from our analysis can be used to understand and compare people's perceptions of future mass mobilizations.
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对被倾听的追求:网络抗议叙事检测的一种无监督方法
抗议和大规模动员很少;然而,当它们发生时,可能会导致戏剧性的结果。像推特这样的社交媒体已经成为组织和发展全球在线抗议活动的中心。为了理解人们的看法,解读网上抗议活动中分享的各种叙述变得至关重要。在这项工作中,我们提出了一个基于无监督聚类的框架来理解给定在线抗议中呈现的叙事。通过对围绕政府政策法案的3次抗议活动中的推文集群的比较分析,我们对在线抗议活动中分享的叙述提供了新的见解。通过对印度和英国政府政策引发的在线抗议的案例研究,我们发现了各种抗议活动中熟悉的大规模动员叙事。我们在研究的所有三种抗议活动中都发现了实地活动和呼吁人民参与的叙述集群。我们还在不同的抗议活动中发现了以抗议为中心的叙述,比如对该主题的怀疑。我们的分析结果可以用来理解和比较人们对未来大规模动员的看法。
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