计算机工程与应用2025，Vol.61Issue(11)：31-50,20.DOI:10.3778/j.issn.1002-8331.2407-0550
社交媒体谣言检测:方法、挑战与趋势
Social Media Rumor Detection:Methods,Challenges,and Trends
摘要
Abstract
With the rapid development of social media,the spread of rumors has an impact on the network environment and social order that cannot be ignored.Therefore,it is very important to carry out research on rumor detection and pre-vent its spread to maintain social harmony.This paper systematically reviews the research progress in the field of rumor detection in recent years.Firstly,the definition of rumor and the differences and connections of related concepts are explained.Secondly,the common data sets of rumor detection are listed and text data sets are analyzed,and the rumor detection methods of various machine learning paradigm strategies are discussed,including supervised learning,semi-supervised learning,unsupervised learning,small sample learning and zero sample learning.Thirdly,the application of large model in rumor detection is discussed innovatively,and the processing methods of image,video and other multimodal data in rumor detection and related research are introduced comprehensively.Finally,the challenges faced by rumor detection and the possible development direction in the future are discussed.关键词
社交媒体/谣言检测/多模态/大模型Key words
social media/rumor detection/multimodality/large model分类
计算机与自动化引用本文复制引用
刘鑫楠,洪鑫宇,曹振洋,李荣荣,王子硕,周俊康,唐斌,陆恒杨..社交媒体谣言检测:方法、挑战与趋势[J].计算机工程与应用,2025,61(11):31-50,20.基金项目
国家自然科学基金(62002137) （62002137）
中国博士后科学基金(2022M711360) （2022M711360）
先进计算与智能工程(国家级)实验室基金. （国家级）
