2013/12/07 by Rui Guo, Hongzhi Wang, Guo, Rui +7
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #Peer-to-Peer Network Technologies #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #Web Data Mining and Analysis #cs.SI #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1312.2096
submitted to DASFAA demo
arxiv created 2013/12/07 · openalex publication_date 2013/12/07 · arxiv updated 2013/12/10 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Online Social Network (OSN) is one of the hottest innovations in the past years, and the active users are more than a billion. For OSN, users' behavior is one of the important factors to study. This demonstration proposal presents Harbinger, an analyzing and predicting system for OSN users' behavior. In Harbinger, we focus on tweets' timestamps (when users post or share messages), visualize users' post behavior as well as message retweet number and build adjustable models to predict users' behavior. Predictions of users' behavior can be performed with the discovered behavior models and the results can be applied to many applications such as tweet crawler and advertisement.