Computational Social Science, Department of Humanities, Social and Political Sciences, ETH Zurich, Zurich, 8092, Switzerland.
Complex Human Behaviour Lab, Fondazione Bruno Kessler, Trento, 38123, Italy.
Sci Rep. 2024 Aug 30;14(1):20233. doi: 10.1038/s41598-024-69447-8.
Social media manipulation poses a significant threat to cognitive autonomy and unbiased opinion formation. Prior literature explored the relationship between online activity and emotional state, cognitive resources, sunlight and weather. However, a limited understanding exists regarding the role of time of day in content spread and the impact of user activity patterns on susceptibility to mis- and disinformation. This work uncovers a strong correlation between user activity time patterns and the tendency to spread potentially disinformative content. Through quantitative analysis of Twitter (now X) data, we examine how user activity throughout the day aligns with diurnal behavioural archetypes. Evening types exhibit a significantly higher inclination towards spreading potentially disinformative content, which is more likely at night-time. This knowledge can become crucial for developing targeted interventions and strategies that mitigate misinformation spread by addressing vulnerable periods and user groups more susceptible to manipulation.
社交媒体操纵对认知自主性和客观意见的形成构成了重大威胁。现有文献探讨了在线活动与情绪状态、认知资源、阳光和天气之间的关系。然而，对于一天中的时间在内容传播中的作用以及用户活动模式对错误和虚假信息的易感性的影响，我们的了解还很有限。这项工作揭示了用户活动时间模式和传播潜在虚假信息内容的倾向之间的强烈相关性。通过对 Twitter（现为 X）数据的定量分析，我们研究了用户全天的活动如何与昼夜行为原型相吻合。夜猫子型人群表现出传播潜在虚假信息内容的明显更高倾向，这种倾向在夜间更为明显。这一知识对于制定有针对性的干预措施和策略至关重要，这些措施和策略可以通过解决易受操纵的脆弱时期和用户群体来减轻错误信息的传播。
