A growing body of evidence points to critical vulnerabilities of social media, such as the emergence of partisan echo chambers and the viral spread of misinformation. We show that these vulnerabilities are amplified by abusive behaviors associated with so-called "follow trains" on Twitter, in which long lists of like-minded accounts are mentioned for others to follow. We present the first systematic analysis of a large U.S. hyper-partisan train network. We observe an artificial inflation of influence: accounts heavily promoted by follow trains profit from a median six-fold increase in daily follower growth. This catalyzes the formation of highly clustered echo chambers, hierarchically organized around a dense core of active accounts. Train accounts also engage in other behaviors that violate platform policies: we find evidence of activity by inauthentic automated accounts and abnormal content deletion, as well as amplification of toxic content from low-credibility and conspiratorial sources. Some train accounts have been active for years, suggesting that platforms need to pay greater attention to this kind of abuse.
翻译:越来越多的证据表明了社交媒体的严重脆弱性,例如党派回声室的出现和错误信息病毒的传播。我们表明,与推特上所谓的“跟踪列车”相关的滥用行为加剧了这些脆弱性。在推特上,人们会提到一长串志同道合的账户清单,供其他人跟踪。我们首次对美国庞大的超党派列车网络进行了系统分析。我们观察到了一种人为的影响膨胀:跟踪列车从日常后续增长的六倍中位增长中获利而大力推动的账户。这催生了高度集群的回声室的形成,这种回声室按等级排列在活跃账户的密集核心上。培训账户还涉及违反平台政策的其他行为:我们发现了不道德自动账户和删除异常内容的活动证据,以及低可信度和共犯来源的有毒内容的放大。一些火车账户多年来一直活跃,表明平台需要更多地关注这种滥用行为。