Most of the information operations involve users who may foster polarization and distrust toward science and mainstream journalism, without these users being conscious of their role. Gab is well known to be an extremist-friendly platform that performs little control on the posted content. Thus it represents an ideal benchmark for studying phenomena potentially related to polarization such as misinformation spreading. The combination of these factors may lead to hate as well as to episodes of harm in the real world. In this work we provide a characterization of the interaction patterns within Gab around the COVID-19 topic. To assess the spreading of different content type, we analyze consumption patterns based on both interaction type and source reliability. Overall we find that there are no strong statistical differences in the social response to questionable and reliable content, both following a power law distribution. However, questionable and reliable sources display structural and topical differences in the use of hashtags. The commenting behaviour of users in terms of both lifetime and sentiment reveals that questionable and reliable posts are perceived in the same manner. We can conclude that despite evident differences between questionable and reliable posts Gab users do not perform such a differentiation thus treating them as a whole. Our results provide insights toward the understanding of coordinated inauthentic behavior and on the early-warning of information operation.
翻译:多数信息业务涉及可能助长对科学和主流新闻的两极分化和不信任的用户,而这些用户没有意识到他们的作用。Gab是众所周知的极端主义友好平台,很少控制所张贴的内容。因此,它是研究与极化有关的潜在现象的理想基准,例如错误信息传播。这些因素的结合可能导致仇恨,并导致真实世界中的伤害事件。在这项工作中,我们对Gab内部围绕COVID-19专题的互动模式作了描述。为了评估不同内容类型的传播情况,我们根据互动类型和来源可靠性分析消费模式。总体而言,我们发现社会对有问题和可靠内容的反应在统计上没有很大的差异,两者都是根据权力法分配的结果。然而,有疑问和可靠的来源显示在使用标签方面的结构性和时事差异。用户在一生和情绪方面的评论表明,对可疑和可靠的职位的看法是相同的。我们可以得出结论,尽管在可疑和可靠的职位上存在明显差异,但Gab用户并没有进行这种区分,从而将他们作为一个整体对待。我们发现,在社会对有疑问和可靠内容的反应方面,在社会上没有明显的差异。我们的结果是,对协调的执法行为和早期情报运作的理解。