Twitter话语社区的蝴蝶结结构
Bow-Tie Structures of Twitter Discursive Communities
摘要：
在对Twitter辩论的分析中，最近的文献集中在话语社区，即通过转发相互作用的账户集群。在目前的工作中，我们研究了话语社区在8个不同的主题Twitter数据集在各种语言。令人惊讶的是，我们观察到，几乎所有的话语社区在政治或社会辩论中表现出领结结构。相反，当讨论的论点与体育赛事不同时，它们就不存在了，例如2020年欧洲杯土耳其和意大利数据集。我们进一步分析了在不同的话语社区的各个部门创建的内容的质量，使用事实检查网站Newsguard的域注释：我们观察到，当话语社区受到m/虚假信息的影响时，具有最低质量的内容是在SCC中产生和共享的内容，特别是，在SCC和OUT扇区之间的转发流中存在低信誉或非信誉消息的强烈发生。从这个意义上说，在受虚假信息影响的话语社区中，大部分账户都可以获得各种各样的内容，但其质量一般相当低;这种情况完美地描述了信息流行病的现象，即获得“关于问题的过多信息，这使得难以确定解决方案”，据卫生组织称。
英文摘要：
In the analysis of Twitter debate, the recent literature focused on discursive communities, i.e. clusters of accounts interacting among themselves via retweets. In the present work, we studied discursive communities in 8 different thematic Twitter datasets in various languages. Surprisingly, we observed that almost all discursive communities therein display a bow-tie structure during political or societal debates. Instead, they are absent when the argument of the discussion is different as sport events, as in the case of Euro2020 Turkish and Italian datasets. We furthermore analysed the quality of the content created in the various sectors of the different discursive communities, using the domain annotation from the fact-checking website Newsguard: we observe that, when the discursive community is affected by m/disinformation, the content with the lowest quality is the ones produced and shared in SCC and, in particular, a strong incidence of low- or non-reputable messages is present in the flow of retweets between the SCC and the OUT sectors. In this sense, in discursive communities affected by m/disinformation, the greatest part of the accounts has access to a great variety of contents, but whose quality is, in general, quite low; such a situation perfectly describes the phenomenon of infodemic, i.e. the access to "an excessive amount of information about a problem, which makes it difficult to identify a solution", according to WHO).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
