真实与虚拟社交网络谣言的研究现状与挑战

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Qiang He, Songyangjun Zhang, Yuliang Cai, Wei Yuan, Lianbo Ma, Keping Yu
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引用次数: 0

摘要

本调查回顾了社交网络中的谣言传播现象,定义了谣言及其表现形式,并强调了谣言造成的社会混乱、恐慌和危害。它探讨了造成谣言的心理、社会和技术因素及其对声誉、恐慌和决策的影响。本文回顾了谣言传播的理论框架,分析了社会网络中的渐进式和非渐进式传播模型。介绍了元宇宙,讨论了它对信息传播的影响以及对谣言传播带来的新挑战。重点介绍了使用人工智能、网络分析和多模式表示的检测和干预方法,以及政策和公共教育策略。此外,该调查还解决了假新闻、深度造假以及社交机器人和自动账户的作用等挑战。讨论了未来的研究方向,包括复杂检测算法的发展、实时监控、跨平台和跨文化谣言检测、隐私保护和自动化应对机制。该调查主张采用技术、社会和法律手段相结合的综合策略来管理谣言传播的复杂性,维护信息的真实性和社会稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Exploring Real and Virtual Social Network Rumors: State-of-the-Art and Research Challenges
This survey reviews the phenomenon of rumor propagation in social networks, defining rumors and their manifestations, and highlighting the societal confusion, panic, and harm they cause. It explores the psychological, social, and technical factors contributing to rumors and their impact on reputation, panic, and decision-making. The review covers theoretical frameworks of rumor propagation, analyzing progressive and non-progressive diffusion models in social networks. It also introduces the metaverse, discussing its impact on information spread and the new challenges it poses for rumor dissemination. Detection and intervention methods using AI, network analysis, and multimodal representation are highlighted, alongside policy and public education strategies. Additionally, the survey addresses challenges such as fake news, deepfakes, and the role of social bots and automated accounts. Future research directions are discussed, including the development of sophisticated detection algorithms, real-time monitoring, cross-platform and cross-cultural rumor detection, privacy protection, and automated coping mechanisms. The survey advocates for integrated strategies combining technological, social, and legal approaches to manage rumor propagation complexities and maintain information authenticity and social stability.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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