Mathematical modelling of information flow in social networks

这项提议旨在开发新的数学和统计方法，以了解社交网络中的信息流。通过使用新的信息论技术，它将创造新的方法来表征社会网络中的社会信息流。这些工具将允许推导出应用于数字数据的人工智能方法的基本可预测性界限。信息流的新数学将对在线社交网络的社会影响产生深刻的见解。好处包括：更好地了解回音室可能如何在社交网络中形成，错误信息如何在网上传播(如在紧急情况下)的预测模型，以及应用于个人数字数据的人工智能方法的相互比较框架。

This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals.