Opinion polarisation and echo chambers in online social media: structure, dynamics and mitigation strategies

在线社交媒体中的意见极化和回声室：结构、动态和缓解策略

• 批准号: 2263179
• 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: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2263179
• 关键词: Opinion; polarisation; echo; chambers; online

In a more and more connected world, relationships and opinions are shaped and evolve through online interactions. Similar-minded users tend to cluster together and form strongly opinionated online communities, the so-called echo chambers. The ensuing polarisation of opinions fosters the spread of conspiracy theories and hinder fruitful political debate. Research on opinion dynamics is focusing more and more on this problem, with most models considering user-level psychological and social features. Those are however difficult to evaluate in practice and there has been a dearth of empirical evaluation of these theoretical works. In this PhD research project I will present a new mathematical framework for the description of echo chambers and quantification of polarisation from a macroscopic point of view. I will also evaluate my model on real-world data and propose leads for algorithmic methods aimed at mitigating the polarisation of opinions.

在一个联系越来越紧密的世界里，人际关系和观点是通过在线互动形成和发展的。志同道合的用户往往聚集在一起，形成非常固执己见的在线社区，即所谓的回音室。随之而来的意见两极分化助长了阴谋论的传播，阻碍了富有成效的政治辩论。意见动力学的研究越来越多地关注这一问题，大多数模型都考虑了用户层面的心理和社会特征。然而，在实践中很难对这些理论著作进行评价，而且对这些理论著作的实证评价一直很少。在这个博士研究项目中，我将提出一个新的数学框架，用于从宏观角度描述回音室和量化偏振。我还将根据真实世界的数据评估我的模型，并为旨在缓解意见两极分化的算法方法提出指导意见。