论文标题
面具后面：一项计算研究，对Twitter上匿名的存在
Behind the Mask: A Computational Study of Anonymous' Presence on Twitter
论文作者
论文摘要
黑客主义团体匿名的面向公共性质是不寻常的。与其他依靠保密和隐私保护保护的网络犯罪群体不同，匿名在社交媒体网站Twitter上普遍存在。在本文中，我们使用对Twitter上匿名的存在的大规模计算分析进行了以前对小组的小规模定性研究报告的一些关键发现。我们特别指的是拒绝该集团无领导人主张的报告，并在2011 - 2013年被捕后表明该集团的破裂。在我们的研究中，我们提出了使用机器学习来识别和分析一个超过20,000个匿名帐户网络的尝试，该网络涉及2008 - 2019年在Twitter平台上。反过来，这项研究利用社交网络分析（SNA）和中心度度量来检查该大型网络中影响力的分布，从而确定了少数高度影响力的账户的存在。此外，我们介绍了来自一些确定的主要影响者帐户的推文的首次研究，并通过使用主题建模，证明了这些著名帐户之间的讨论的总体讨论主题相似。这些发现提供了强大的定量证据，以支持匿名集体较小规模的定性研究的主张。
The hacktivist group Anonymous is unusual in its public-facing nature. Unlike other cybercriminal groups, which rely on secrecy and privacy for protection, Anonymous is prevalent on the social media site, Twitter. In this paper we re-examine some key findings reported in previous small-scale qualitative studies of the group using a large-scale computational analysis of Anonymous' presence on Twitter. We specifically refer to reports which reject the group's claims of leaderlessness, and indicate a fracturing of the group after the arrests of prominent members in 2011-2013. In our research, we present the first attempts to use machine learning to identify and analyse the presence of a network of over 20,000 Anonymous accounts spanning from 2008-2019 on the Twitter platform. In turn, this research utilises social network analysis (SNA) and centrality measures to examine the distribution of influence within this large network, identifying the presence of a small number of highly influential accounts. Moreover, we present the first study of tweets from some of the identified key influencer accounts and, through the use of topic modelling, demonstrate a similarity in overarching subjects of discussion between these prominent accounts. These findings provide robust, quantitative evidence to support the claims of smaller-scale, qualitative studies of the Anonymous collective.
