Yongjun Li

Papers

Total Citations

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About

Yongjun Li is a researcher whose work centers on the detection and behavioral analysis of social robots—automated or AI-driven accounts that mimic human interaction on social media platforms. His most-cited paper, "Social robot detection based on user behavioral representation" (2024), introduces a novel framework that models user activity patterns to distinguish between genuine human users and social bots. This contribution addresses a critical challenge in cybersecurity and online trust, offering a scalable approach to identifying deceptive accounts through behavioral signatures rather than relying solely on content analysis. While his citation count is still growing, with 2 citations to date, the work has already gained attention for its practical implications in social media moderation and digital forensics. Li’s research sits at the intersection of machine learning, social network analysis, and human-computer interaction, aiming to improve the integrity of online communities. His focus on behavioral representation marks a promising direction for future studies in bot detection, particularly as social robots become more sophisticated.