The year 2020 will be remembered for two events of global significance: the COVID-19 pandemic and 2020 U.S. Presidential Election. In this chapter, we summarize recent studies using large public Twitter data sets on these issues. We have three primary objectives. First, we delineate epistemological and practical considerations when combining the traditions of computational research and social science research. A sensible balance should be struck when the stakes are high between advancing social theory and concrete, timely reporting of ongoing events. We additionally comment on the computational challenges of gleaning insight from large amounts of social media data. Second, we characterize the role of social bots in social media manipulation around the discourse on the COVID-19 pandemic and 2020 U.S. Presidential Election. Third, we compare results from 2020 to prior years to note that, although bot accounts still contribute to the emergence of echo-chambers, there is a transition from state-sponsored campaigns to domestically emergent sources of distortion. Furthermore, issues of public health can be confounded by political orientation, especially from localized communities of actors who spread misinformation. We conclude that automation and social media manipulation pose issues to a healthy and democratic discourse, precisely because they distort representation of pluralism within the public sphere.
翻译:2020年将是具有全球意义的两件大事:COVID-19大流行和2020年美国总统选举。本章我们总结了最近使用大型公共推特数据组研究的关于这些问题的最新研究。我们有三个主要目标。首先,我们在将计算研究和社会科学研究的传统结合起来时,将认知和实践因素考虑在内。当推进社会理论和具体、及时报告当前事件之间的利害关系重大时,应当取得合理的平衡。我们进一步评论从大量社会媒体数据中收集洞察力的计算挑战。第二,我们描述了社会机器人在围绕关于COVID-19大流行和2020年美国总统选举的讨论中在社会媒体操纵中的作用。第三,我们比较了2020年到前几年的结果,指出,尽管博特账户仍然有助于回声机的出现,但从国家赞助的运动向国内新出现的扭曲来源过渡。此外,公共健康问题可以被政治取向,特别是传播错误信息的当地社会行为者社区所困扰。我们的结论是,自动化和社会媒体操纵在公共多元化中造成了健康和民主的代表面。我们的结论是,因为它们恰恰是因为它们扭曲了公共多元化。