Mathematical modelling of information flow in social networks

本提案旨在发展新的数学和统计方法来理解社交网络中的信息流。通过使用新颖的信息理论技术，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应用于数字数据的人工智能方法的可预测性的基本限制。信息流的新数学将产生对在线社交网络的社会影响的见解。好处包括：更好地了解社交网络中的回音室可能如何形成，预测错误信息如何在紧急情况下在线传播的模型，以及将人工智能方法应用于个人数字数据的相互比较框架。

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.