识别和描述Twitter上低可信度内容的超级传播者
Matthew R DeVerna1, Rachith Aiyappa1, Diogo Pacheco1,2
1Observatory on Social Media, Indiana University, Bloomington, Indiana, United States of America.
PloS one
|May 22, 2024
概括
研究人员确定了"超级传播者",他们在网上不成比例地分享低可信度的内容. 简单的指标可以预测这些错误信息的超级传播者,帮助努力打击有害的数字话语.
科学领域:
- 数字通信 数字通信
- 信息科学 信息科学
- 社交媒体分析
背景情况:
- 数字信息生态系统面临着广泛的错误信息的挑战.
- 之前的研究表明",超级传播者"对于传播低可信度内容至关重要.
研究的目的:
- 量化证实超级传播者在错误信息中的作用.
- 开发用于预测未来超级传播者的指标.
- 为了定性地描述多产超级传播者的行为.
主要方法:
- 量化分析以证实超级传播者假说.
- 开发用于识别顶级超级传播者的预测指标.
- 对最多产的超级传播者的分享行为进行定性审查.
主要成果:
- 超级传播者包括政治专家,低可信度媒体和影响者.
- 与典型的错误信息分享者相比,超级传播者表现出更有毒的语言.
- 有证据表明,著名的超级传播者可能会被像Twitter这样的平台所忽视.
结论:
- 超级传播者是网络虚假信息传播的关键参与者.
- 预测指标可以帮助识别和减轻这些行为者的影响.
- 了解超级传播者的行为对于培养更健康的数字话语至关重要.
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