Social Network
Social network analysis investigates the structure and dynamics of interconnected individuals or entities, aiming to understand information diffusion, influence propagation, and collective behavior. Current research focuses on developing sophisticated models, including graph neural networks, Markov decision processes, and large language models, to analyze diverse aspects such as misinformation detection, opinion dynamics, and recommendation systems. These advancements have significant implications for various fields, improving our understanding of social phenomena and enabling the development of more effective tools for combating online harms and enhancing user experience on social media platforms.
Papers
DANI: Fast Diffusion Aware Network Inference with Preserving Topological Structure Property
Maryam Ramezani, Aryan Ahadinia, Erfan Farhadi, Hamid R. Rabiee
A Unified View on Neural Message Passing with Opinion Dynamics for Social Networks
Outongyi Lv, Bingxin Zhou, Jing Wang, Xiang Xiao, Weishu Zhao, Lirong Zheng
Social Network Analysis and Validation of an Agent-Based Model
Karleigh Pine, Joel Klipfel, Jared Bennett, Nathaniel Bade, Christian Manasseh
CasCIFF: A Cross-Domain Information Fusion Framework Tailored for Cascade Prediction in Social Networks
Hongjun Zhu, Shun Yuan, Xin Liu, Kuo Chen, Chaolong Jia, Ying Qian