Modeling and control of time sensitive sequences found in social media and conversation dynamics

The PhD project investigates the time sensitive sequential events which occur in social media platforms such as the dissemination of Misinformation over Twitter.

We study novel Artificial Intelligence methods with less memory footprints and interpretable results to model the dynamics of online content circulation. Furthermore we control the spread of Misinformation by mitigating the latter through learned strategies.

The final outcome of this project would facilitate the process of emergency management by providing story telling simulations to evaluate different intervention strategies to predict and combat online Misinformation.

Our research methodology involves Hawkes Processes, Learning Automata, and the Tsetlin Machine.

Supervisors: Professor Ole-Christoffer Granmo and Professor Christian Webersik.