COVID-19大流行期间社交机器人和人类的比较分析。

IF 2.3 Q2 SOCIAL SCIENCES, MATHEMATICAL METHODS
Journal of Computational Social Science Pub Date : 2022-01-01 Epub Date: 2022-06-30 DOI:10.1007/s42001-022-00173-9
Ho-Chun Herbert Chang, Emilio Ferrara
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引用次数: 12

摘要

本文利用500多万用户的40多亿条推文和标签,从政治和语义上比较了疫情期间人类和机器人的行为。结果显示,总体而言,自由主义机器人比人类更重要,但随着精英圈子越来越小,它们的重要性不如制度人类。与之前的政治话语研究相比,保守派机器人令人惊讶地缺席,但在从人类那里得到回复方面,它们比自由派机器人做得更好,这表明它们可能更容易被视为人类。在话题和框架方面,保守的人类和机器人不成比例地发布关于比尔·盖茨和生物武器阴谋的推文,而5G阴谋则是两党共同参与的。保守的人有选择地忽略戴口罩,我们观察到在讨论政策时普遍存在的群体外推文。我们讨论并对比了与政治事件相比,人类如何在与健康相关的话语中显得更加集中,这表明在在线信息传播中,可信度和真实性对公共卫生的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Comparative analysis of social bots and humans during the COVID-19 pandemic.

Comparative analysis of social bots and humans during the COVID-19 pandemic.

Comparative analysis of social bots and humans during the COVID-19 pandemic.

Comparative analysis of social bots and humans during the COVID-19 pandemic.

Using more than 4 billion tweets and labels on more than 5 million users, this paper compares the behavior of humans and bots politically and semantically during the pandemic. Results reveal liberal bots are more central than humans in general, but less important than institutional humans as the elite circle grows smaller. Conservative bots are surprisingly absent when compared to prior work on political discourse, but are better than liberal bots at eliciting replies from humans, which suggest they may be perceived as human more frequently. In terms of topic and framing, conservative humans and bots disproportionately tweet about the Bill Gates and bio-weapons conspiracy, whereas the 5G conspiracy is bipartisan. Conservative humans selectively ignore mask-wearing and we observe prevalent out-group tweeting when discussing policy. We discuss and contrast how humans appear more centralized in health-related discourse as compared to political events, which suggests the importance of credibility and authenticity for public health in online information diffusion.

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来源期刊
Journal of Computational Social Science
Journal of Computational Social Science SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
6.20
自引率
6.20%
发文量
30
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