当前位置: X-MOL 学术Comput. Math. Organ. Theory › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections
Computational and Mathematical Organization Theory ( IF 1.8 ) Pub Date : 2021-05-04 , DOI: 10.1007/s10588-021-09332-1
Joshua Uyheng 1 , Lynnette Hui Xian Ng 1 , Kathleen M Carley 1
Affiliation  

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.



中文翻译:

积极、进取但收效甚微:2020 年新加坡大选期间机器人活动的特征

数字虚假信息给全世界的民主国家带来了一个具有挑战性的问题,尤其是在像 COVID-19 大流行这样的危机时期。在新加坡等国家,打击假新闻的立法努力构成了了解当地信息运营的相对较新且未被充分研究的背景。本文介绍了对 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最严重的时期以及最近通过反假新闻法之后。利用包含 240,000 条关于选举的推文的数据集,我们发现 26.99% 的参与账户可能是机器人,与 2015 年的选举相比,机器人推文的比例更大。文本分析进一步表明,检测到的机器人使用更简单、更多辱骂性的第二人称语言,以及与 COVID-19 和选民活动相关的标签——指出激进的策略可能会加剧在线敌意并质疑投票的合法性。最后,机器人与更大、密度更低、回声室般的社区相关联,这表明人们努力参与更大的主流对话。然而,尽管它们具有独特的叙事和网络策略,但机器人通常不会在整个社交网络中产生重大影响。因此,尽管在全球大流行期间对政治冲突的交叉担忧可能会迅速增加网络干扰的可能性,但我们量化了 2020 年新加坡选举中由机器人驱动的虚假信息的努力和限制。最后,我们总结了亚太地区及其他地区在危机时期对数字虚假信息的若干影响。

更新日期:2021-05-05
down
wechat
bug