47 citations · 103 across the 27 of their papers we have counts for
6 papers · 1 filter
HOFA: Twitter Bot Detection with Homophily-Oriented Augmentation and Frequency Adaptive Attention
Sen Ye, Zhaoxuan Tan, Zhenyu Lei +4
Twitter bot detection has become an increasingly important and challenging task to combat online misinformation, facilitate social content moderation, and safeguard the integrity o…
BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts
Yuhan Liu, Zhaoxuan Tan, Heng Wang +3
Twitter bot detection has become a crucial task in efforts to combat online misinformation, mitigate election interference, and curb malicious propaganda. However, advanced Twitter…
BotPercent: Estimating Bot Populations in Twitter Communities
Zhaoxuan Tan, Shangbin Feng, Melanie Sclar +4
Twitter bot detection is vital in combating misinformation and safeguarding the integrity of social media discourse. While malicious bots are becoming more and more sophisticated a…
AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach
Shujie Yang, Binchi Zhang, Shangbin Feng +4
Graph anomaly detection on attributed networks has become a prevalent research topic due to its broad applications in many influential domains. In real-world scenarios, nodes and e…
TwiBot-22: Towards Graph-Based Twitter Bot Detection
Shangbin Feng, Zhaoxuan Tan, Herun Wan +19
Twitter bot detection has become an increasingly important task to combat misinformation, facilitate social media moderation, and preserve the integrity of the online discourse. St…
Heterogeneity-aware Twitter Bot Detection with Relational Graph Transformers
Shangbin Feng, Zhaoxuan Tan, Rui Li +1
Twitter bot detection has become an important and challenging task to combat misinformation and protect the integrity of the online discourse. State-of-the-art approaches generally…