Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections
Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections
复制标题
衡量针对美国中期选举候选人的对抗性 Twitter 互动
DOI：
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Mor Naaman
中科院分区：
文献类型：
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作者：
Yiqing Hua;Thomas Ristenpart;Mor Naaman
在推特（Twitter）等社交媒体上，针对政客的对抗性互动对社会产生了重大影响。特别是，它们扰乱了网上实质性的政治讨论，并可能阻碍人们竞选公职。在这项研究中，我们测量了在2018年美国大选前夕针对美国众议院候选人的对抗性互动。我们收集了一个新的数据集，由170万条涉及候选人的推文组成，这是关注政治话语的最大语料库之一。然后，我们开发了一种新技术，用于检测针对任何特定候选人的含有有毒内容的推文。这种技术使我们能够更准确地量化对政治候选人的敌对互动。此外，我们引入了一种算法来诱导候选人特定的对抗性术语，以捕获更细微的对抗性相互作用，而以前的技术可能认为这些作用是无害的。最后，我们使用这些技术来概述在选举中看到的对抗性互动的广度，包括攻击性的辱骂、暴力威胁、发布不可信的信息、对身份的攻击和对抗性信息的重复。
Adversarial interactions against politicians on social media such as Twitter have significant impact on society. In particular they disrupt substantive political discussions online, and may discourage people from seeking public office. In this study, we measure the adversarial interactions against candidates for the US House of Representatives during the run-up to the 2018 US general election. We gather a new dataset consisting of 1.7 million tweets involving candidates, one of the largest corpora focusing on political discourse. We then develop a new technique for detecting tweets with toxic content that are directed at any specific candidate. Such technique allows us to more accurately quantify adversarial interactions towards political candidates. Further, we introduce an algorithm to induce candidate-specific adversarial terms to capture more nuanced adversarial interactions that previous techniques may not consider toxic. Finally, we use these techniques to outline the breadth of adversarial interactions seen in the election, including offensive name-calling, threats of violence, posting discrediting information, attacks on identity, and adversarial message repetition.
DOI：
10.1145/3313831.3376548
发表时间：
2020-04
期刊：
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
影响因子：
--
作者：
Yiqing Hua;Mor Naaman;Thomas Ristenpart
通讯作者：
Yiqing Hua;Mor Naaman;Thomas Ristenpart