In this work we study how pervasive is the presence of disinformation in the Italian debate around immigration on Twitter and the role of automated accounts in the diffusion of such content. By characterising the Twitter users with an \textit{Untrustworthiness} score, that tells us how frequently they engage with disinformation content, we are able to see that such bad information consumption habits are not equally distributed across the users; adopting a network analysis approach, we can identify communities characterised by a very high presence of users that frequently share content from unreliable news sources. Within this context, social bots tend to inject in the network more malicious content, that often remains confined in a limited number of clusters; instead, they target reliable content in order to diversify their reach. The evidence we gather suggests that, at least in this particular case study, there is a strong interplay between social bots and users engaging with unreliable content, influencing the diffusion of the latter across the network.
翻译:在这项工作中,我们研究在意大利关于Twitter移民的辩论中是否存在虚假信息,以及自动账户在传播此类内容方面的作用。通过将Twitter用户描述为\ textit{Un信任}分,告诉我们他们如何频繁地使用虚假信息内容,我们可以看到,这种不良的信息消费习惯在用户中分布不均;我们采用网络分析方法,可以确定以经常分享不可靠新闻来源内容的用户比例极高的社区特征。在这方面,社会机器人往往在网络中注入更多的恶意内容,这些内容往往局限于有限的组群;相反,他们瞄准可靠的内容,以便分散其覆盖面。我们收集的证据表明,至少在这个特定案例研究中,社会机体和用户之间有着很强的相互作用,其内容不可靠,影响后者在整个网络的传播。