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首页> 外文期刊>Computational & Mathematical Organization Theory >Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections
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Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections

机译:活跃,侵略性,但有点没用:在2020年的新加坡选举中表征机器人活动

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摘要

Digital disinformation presents a challenging problem for democracies worldwide, especially in times of crisis like the COVID-19 pandemic. In countries like Singapore, legislative efforts to quell fake news constitute relatively new and understudied contexts for understanding local information operations. This paper presents a social cybersecurity analysis of the 2020 Singaporean elections, which took place at the height of the pandemic and after the recent passage of an anti-fake news law. Harnessing a dataset of 240,000 tweets about the elections, we found that 26.99% of participating accounts were likely to be bots, responsible for a larger proportion of bot tweets than the election in 2015. Textual analysis further showed that the detected bots used simpler and more abusive second-person language, as well as hashtags related to COVID-19 and voter activity-pointing to aggressive tactics potentially fuelling online hostility and questioning the legitimacy of the polls. Finally, bots were associated with larger, less dense, and less echo chamber-like communities, suggesting efforts to participate in larger, mainstream conversations. However, despite their distinct narrative and network maneuvers, bots generally did not hold significant influence throughout the social network. Hence, although intersecting concerns of political conflict during a global pandemic may promptly raise the possibility of online interference, we quantify both the efforts and limits of bot-fueled disinformation in the 2020 Singaporean elections. We conclude with several implications for digital disinformation in times of crisis, in the Asia-Pacific and beyond.
机译:数字消号为全世界民主国家提供了一个挑战性问题,特别是在Covid-19大流行等危机时期。在新加坡这样的国家,普尔假新闻的立法努力构成了了解本地信息行动的相对良好和深受利用的背景。本文介绍了2020年新加坡选举的社会网络安全分析,该选举发生在大流行的高度和最近的反假新闻法之后。利用关于选举的240,000条推文的数据集,我们发现,26.99%的参与账户可能是机器人,负责大部分的机器人推文,比2015年的选举。文本分析进一步表明检测到的机器人使用更简单和更多滥用第二人称语言,以及与Covid-19和选民活动相关的哈希特,指向潜在的攻击战术,可能会加以在线敌意并质疑民意调查的合法性。最后,机器人与更大,更密集,较少的回声室内的社区相关联,表明努力参与更大的主流对话。然而,尽管他们具有明显的叙述和网络演习,但机器人通常在整个社交网络中都没有重大影响。因此,虽然在全球流行病中的政治冲突的关切可能会及时提出在线干扰的可能性,但我们在2020年新加坡选举中量化了机器人燃料的努力和限制。我们在亚太及以后的危机时期,我们的结论是对危机时期的几种影响。

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