电子科技大学学报2026，Vol.55Issue(2)：232-243,12.DOI:10.12178/1001-0548.2024277
基于多模态信息不变和特定表示的社交机器人检测方法
Social bot detection method based on multimodal information invariant and specific representation
摘要
Abstract
Social bots have continuously evolved during their development,posing significant challenges to existing detection models.To address this,we propose a novel social bot detection framework,named BotSAI.This framework first employs customized encoders to extract multi-dimensional feature representations from user metadata,text,and heterogeneous social network graphs.Specifically,the graph encoder achieves efficient and balanced aggregation of neighborhood information through oversampling and a local relation transformer.Subsequently,a multi-channel representor maps user representations into invariant subspaces and specific subspaces to enhance their features.Finally,the enhanced user representations are integrated and refined using a self-attention mechanism.Experimental results demonstrate that BotSAI outperforms state-of-the-art methods on two authoritative social bot detection benchmarks.Furthermore,systematic experiments reveal the impact of different social relationships on detection accuracy,providing new research perspectives for social bot detection.关键词
社交机器人检测/社交网络异构图/不变与特定子空间/自注意力机制Key words
social bot detection/heterogeneous graph of social networks/invariant and specific subspaces/self-attention mechanism分类
信息技术与安全科学引用本文复制引用
屈津,杜姝颖,宫继兵,彭吉全,王开宇..基于多模态信息不变和特定表示的社交机器人检测方法[J].电子科技大学学报,2026,55(2):232-243,12.基金项目
河北省创新能力提升计划资助项目(22567626H) （22567626H）
中央引导地方科技发展资金项目(246Z0306G) （246Z0306G）
