Simulation and Modeling of Information Dissemination in Online Social Networks

With the development of internet technology, the emergence of social media and online platforms promotes the interchange of information between online users at a fast speed. This allows important and useful information to spread through communities quickly; however, it also permits harmful information, like fake news, to also quickly propagate. Users' responses and attitudes towards the information and subsequent responses may influence how other users perceive and further disseminate the information.
This research aims at investigating the influence that users' networks and stances towards an issue (e.g. fake news, restaurant quality) have on information dissemination in Online Social Networks (OSNs). This research has specifically considered: 1) Discovering the influence that particular user reviews have on future ratings for restaurants on Yelp; 2) Understanding the spread of fake news on Twitter through simulation and modeling. Multivariate Hawkes Processes, a mutually-exciting class of point process models, are used to model the intensity of the information propagation based on measurable features on the network, user stances, and message content. This research models the information dissemination process on social media, quantifies the influence the users received from the user networks, identifies the influential factors, and provides insights into the behavioral patterns between online users during the process.