Seungwoong Ha
November 19, 2024 1:00pm Luddy Center for Artificial Intelligence, Room 2005
Zoom: https://iu.zoom.us/j/89107137699
Title: Dynamics of Collective Minds: A Computational Model of news-comment Dynamics"
Abstract: In an online community, many of the community users collectively consist of a unique set of interests and beliefs, which can be expressed as a 'collective mind' of the community. We are interested in what the collective mind of community users is aiming for, especially in terms of diverse topics, and what would be the dynamics of the frequency of the comments on certain topics (along with the similarity between those topics). After gathering data from nearly 10 years of news and comment data from 5 different online news communities, we aim to build a simple yet comprehensive computational model for the online news community where news articles and comments are posted daily. In this model, the outside world that generates 'news', the community-specific filter then determines which news will get posted or not on their community, the 'collective mind' of the community reacts to the filtered news and generates comments, and finally, these comments alter the collective mind itself, repetitively. With this model, our goal is to explore the variety of interventions that may affect the community mind, such as comment filtering, strong editorial policies, and trolls/bots regulations.
Bio: Seungwoong Ha is currently an applied complexity postdoctoral fellow at Santa Fe Institute. Seungwoong received his B.S., M.S., and Ph.D. in Physics from KAIST, and previously at the School of Computational Sciences at the Korea Institute for Advanced Study (KIAS) as a Postdoctoral research fellow. Seungwoong's interests range from statistical physics, complex systems, network science, social science, artificial intelligence, and deep learning as well. During his Ph. D., he attempted to solve problems in complex systems by constructing novel and interpretable neural networks. Now he is slightly shifting his focus to more social systems and wants to formulate/model the emergence/evolution of diverse social phenomena. At SFI, He mainly explores how people's knowledge and opinions change in the community from both belief dynamics and machine learning perspectives.