Computational Mechanisms of Online Attention Markets

While the internet offers access to a world of information, it has been increasingly used against consumers and citizens to spread falsehoods and harmful messages. Mass harm and misinformation has been possible because while we know how to predict individual behaviour to take action with online content (e.g. to like, share, retweet), we do not have that predictive capability on a mass scale, making it impossible to control content from going viral. This project will establish mathematical foundations for the dynamics of online attention and create new algorithms that enable online-content producers, consumers, platforms and regulators to influence and control online action with content. Through demonstrations and dialogues with regulators, the software tools we develop will help them predict attention trends and inform their future online regulatory policy settings. The new knowled