Social Influence and Opinion Forming in Online Social Networks.

Web-based phenomena such as fake news, hate speech or echo chambers have been gaining increasing attention in the public discourse. However, the extent and actual impact of these phenomena are still unknown. In order to address these issues in more depth, it is important to understand how opinions emerge, change and get exchanged. In our work, we therefore intend to develop data-driven approaches to examine social influence mechanisms and opinion forming at a large scale.<br> <br> <br> <br> We aim, in particular, to introduce a complex user model, which characterizes each person with respect to three levels: 1) the individual level capturing the characteristics of a user; 2) the network level capturing the social relationships of a user; and 3) the group level describing sets of similar users with certain dominant opinions and high-level ideologies. We introduce the concepts based on a rich and unique dataset of an online news forum that contains the complete posting history of all users, their detailed behaviors and interactions as well as all news articles and the respective meta data for almost two decades.