揭露超级传播者：用于识别和比较X.com上阴谋论关键影响者的数据驱动方法
Unmasking Superspreaders: Data-Driven Approaches for Identifying and Comparing Key Influencers of Conspiracy Theories on X.com
AI总结：
本研究通过分析新冠疫情期间的七百多万条推文，揭示了人类超级传播者与机器人在语言复杂性、毒性及话题标签使用等方面的差异，并提出27种新指标用于量化阴谋论传播的严重性，为平台管理及公众意识活动提供基础。
摘要：
阴谋论可以通过传播错误信息、加深政治极化和侵蚀民主机构的信任来威胁社会。社交媒体往往助长阴谋的传播，主要由两个关键角色驱动：超级传播者——传播阴谋内容的有影响力个体，以不成比例高的速度传播，以及机器人——设计用来战略性地放大阴谋的自动账户。为了对抗阴谋论的传播，识别这些角色并更好地理解其行为至关重要。然而，对这些角色的系统分析以及适用于现实世界的识别方法仍然缺乏。在本研究中，我们利用新冠疫情期间的七百多万条推文，分析人类超级传播者和机器人在语言复杂性、毒性、话题标签使用等维度上的关键差异。我们的分析揭示了不同的沟通策略：超级传播者倾向于使用更复杂的语言和实质内容，而依赖较少的结构性元素如话题标签和表情符号，这可能有助于提高可信度和权威性。相比之下，机器人偏好更简单的语言和策略性使用话题标签，这可能有助于提高可访问性，促进渗透到热门讨论中，并扩大传播范围。为了对抗人类超级传播者和机器人，我们提出了并评估了27种新的指标，用于量化阴谋论传播的严重性。我们的发现突显了适应性H-指数在计算上可行的识别人类超级传播者中的有效性。通过识别人类超级传播者和机器人独特的行为模式，并提供合适的方法，本研究为缓解策略奠定了基础，包括平台管理政策、临时和永久账户暂停以及公众意识活动。
英文摘要：
Conspiracy theories can threaten society by spreading misinformation, deepening polarization, and eroding trust in democratic institutions. Social media often fuels the spread of conspiracies, primarily driven by two key actors: Superspreaders -- influential individuals disseminating conspiracy content at disproportionately high rates, and Bots -- automated accounts designed to amplify conspiracies strategically. To counter the spread of conspiracy theories, it is critical to both identify these actors and to better understand their behavior. However, a systematic analysis of these actors as well as real-world-applicable identification methods are still lacking. In this study, we leverage over seven million tweets from the COVID-19 pandemic to analyze key differences between Human Superspreaders and Bots across dimensions such as linguistic complexity, toxicity, and hashtag usage. Our analysis reveals distinct communication strategies: Superspreaders tend to use more complex language and substantive content while relying less on structural elements like hashtags and emojis, likely to enhance credibility and authority. By contrast, Bots favor simpler language and strategic cross-usage of hashtags, likely to increase accessibility, facilitate infiltration into trending discussions, and amplify reach. To counter both Human Superspreaders and Bots, we propose and evaluate 27 novel metrics for quantifying the severity of conspiracy theory spread. Our findings highlight the effectiveness of an adapted H-Index for computationally feasible identification of Human Superspreaders. By identifying behavioral patterns unique to Human Superspreaders and Bots as well as providing suitable identification methods, this study provides a foundation for mitigation strategies, including platform moderation policies, temporary and permanent account suspensions, and public awareness campaigns.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
