Meta-Terrorism: Identifying Linguistic Patterns in Public Discourse After an Attack

Panos Kostakos, Markus Nykanen, Mikael Martinviita, Abhinay Pandya, M. Oussalah
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引用次数: 10

Abstract

When a terror-related event occurs, there is a surge of traffic on social media comprising of informative messages, emotional outbursts, helpful safety tips, and rumors. It is important to understand the behavior manifested on social media sites to gain a better understanding of how to govern and manage in a time of crisis. We undertook a detailed study of Twitter during two recent terror-related events: the Manchester attacks and the Las Vegas shooting. We analyze the tweets during these periods using (a) sentiment analysis, (b) topic analysis, and (c) fake news detection. Our analysis demonstrates the spectrum of emotions evinced in reaction and the way those reactions spread over the event timeline. Also, with respect to topic analysis, we find “echo chambers”, groups of people interested in similar aspects of the event. Encouraged by our results on these two event datasets, the paper seeks to enable a holistic analysis of social media messages in a time of crisis.
元恐怖主义:攻击后公共话语的语言模式识别
当发生与恐怖有关的事件时,社交媒体上的流量激增,包括信息信息、情绪爆发、有用的安全提示和谣言。了解社交媒体网站上表现出来的行为对于更好地理解如何在危机时期进行治理和管理是很重要的。我们对最近两起与恐怖有关的事件——曼彻斯特袭击和拉斯维加斯枪击案——期间的Twitter进行了详细研究。我们使用(a)情感分析,(b)主题分析和(c)假新闻检测来分析这些期间的推文。我们的分析展示了反应中表现出的各种情绪,以及这些反应在事件时间轴上的传播方式。此外,在主题分析方面,我们发现了“回音室”,即对事件的相似方面感兴趣的人群。受我们在这两个事件数据集上的结果的鼓舞,本文试图在危机时刻对社交媒体信息进行全面分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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