Social Media and Social Network Analytics

The Internet has become the backbone of our social interactions, with increasing user participation in online social networks and changing the way users interact. This has attracted attracted considerable research in social network analysis with applications to viral marketing, online advertising, recommender systems, information diffusion, and experts finding. Our projects leverage state-of-the-art artificial intelligence and data science technologies for the detection and mitigation of misinformation in online social media.

We adopt a topology-based approach to analyze social networks for user recommendation and find influential users at a finer granularity over time. We are interested to find brokers, or users who are strategically located in the network as gate-keepers to diffuse information across communities. We have developed a fast heuristic algorithm to find brokers based on the weak tie theory in sociology.

We also study the flow of both credible information and misinformation to design strategies to diminish the influence of misinformation. The results of our work can be used by local industry to understand the public knowledge of their products or services (as expressed in social media), whether this knowledge is credible or not, and how to better propagate favorable information through a network.

Selected Publications