Misinformation or disinformation: Exploring cyber related risk of social media personas

错误信息或虚假信息：探索社交媒体角色的网络相关风险

• 批准号: 2726556
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2726556
• 关键词: Misinformation; disinformation; Exploring; cyber; related

The project will explore online personas on social media to develop new techniques to mitigate misinformation and disinformation. A problem with existing mitigation tools is that noise is abundant on social media, making it difficult to find those with malicious intent. Using open-source intelligence, we will study this intention by exploring user behaviour across multiple social media platforms, considering consistency and different online personas. The study will focus on a result-orientated analysis to uncover those engaging in misinformation/ disinformation noise. We can then separate this noise from the real threat of targeted disinformation, aiming to influence the opinion of social media users. This technique can extend beyond the exploration of noise, such as looking at the radicalisation from soft content to more extreme content, possibly through different platforms with lesser moderation. It could also lead to developing a weighting scale to categorise influence, considering which users are riskier due to their reach and content.

该项目将探索社交媒体上的在线人物角色，以开发新的技术来减少错误信息和虚假信息。现有缓解工具的一个问题是，社交媒体上充斥着噪音，因此很难找到那些有恶意的人。利用开源情报，我们将通过探索跨多个社交媒体平台的用户行为，考虑一致性和不同的在线角色，来研究这一意图。这项研究将重点放在以结果为导向的分析上，以揭露那些从事错误信息/虚假信息噪音的人。然后，我们可以将这种噪音与有针对性的虚假信息的真正威胁分开，目的是影响社交媒体用户的观点。这项技术可以超越对噪音的探索，比如从软内容到更极端的内容的激进化，可能是通过不同的平台，但温和程度较低。这也可能导致开发一个权重表来对影响力进行分类，考虑到哪些用户因其覆盖范围和内容而风险更高。