电子学报 ›› 2020, Vol. 48 ›› Issue (7): 1421-1435.DOI: 10.3969/j.issn.0372-2112.2020.07.023

• 综述评论 • 上一篇    下一篇

社会网络谣言检测综述

高玉君1, 梁刚1, 蒋方婷1, 许春2, 杨进1, 陈俊任1, 王浩3   

  1. 1. 四川大学网络空间安全学院, 四川成都 610065;
    2. 四川大学信息管理中心, 四川成都 610065;
    3. 成都信息工程大学软件工程学院, 四川成都 610225
  • 收稿日期:2019-06-19 修回日期:2019-12-25 出版日期:2020-07-25 发布日期:2020-07-25
  • 通讯作者: 梁刚
  • 作者简介:高玉君 女,1995年10月出生,江西吉安人.四川大学网络空间安全学院硕士研究生.主要研究方向为谣言检测与网络安全.E-mail:yj631@foxmail.com
  • 基金资助:
    四川省科技厅应用基础项目(No.2018JY0193);四川省教育厅重点项目(No.17ZA0238,No.18ZA0305,No.18ZA0301);国家自然科学基金(No.61872254)

Social Network Rumor Detection: A Survey

GAO Yu-jun1, LIANG Gang1, JIANG Fang-ting1, XU Chun2, YANG Jin1, CHEN Jun-ren1, WANG Hao3   

  1. 1. College of Cyber Security, Sichuan University, Chengdu, Sichuan 610065, China;
    2. Information Management Center, Sichuan University, Chengdu, Sichuan 610065, China;
    3. Software Engineering Institute, Chengdu University of Information Technology, Chengdu, Sichuan 610225, China
  • Received:2019-06-19 Revised:2019-12-25 Online:2020-07-25 Published:2020-07-25

摘要: 当前社会网络已取代传统媒体成为信息交流的重要平台,社会网络中的信息具有传播速度快,范围广,即时性强等优点.然而,由于发布信息时缺乏有效的监管手段,导致社会网络平台同时也成为谣言传播的温床.因此,快速有效地检测出社会网络谣言,对净化网络环境,维护公共安全至关重要.本文首先对谣言定义进行阐述,并描述当前谣言检测的问题及检测过程;其次,介绍不同数据获取方式并分析其利弊,同时对比谣言检测中不同的数据标注方法;第三,根据谣言检测技术的发展对现有的人工、机器学习和深度学习的谣言检测方法进行分析对比;第四,通过实验在相同公开数据集下对当前主流算法进行实证评估;最后,对社会网络谣言检测技术面临的挑战进行归纳并总结全文.

关键词: 社会网络, 谣言检测, 网络空间安全

Abstract: The current social network has replaced traditional media as an important platform for information exchange.The information in social networks has the advantages of fast dissemination,wide range,and strong immediacy.However,due to the lack of effective supervision means when publishing information,the social network platform has also become a hotbed of rumors.Therefore,the rapid and effective detection of social network rumors is essential for purifying the network environment and maintaining public safety.Firstly,this article explains the definition of rumors,and the problems of current rumors detection and detection process are described.Secondly,different data acquisition methods are introduced and their advantages and disadvantages are analyzed.At the same time,different data annotation methods in rumor detection are compared.Thirdly,according to the development of rumor detection technology,analyze and compare the existing rumors detection methods of artificial,machine learning and deep learning.Fourthly,current mainstream algorithms are empirically evaluated under the same open data set through experiments.Finally,analyze and summarize the challenges faced by current social network rumor detection technology.

Key words: social network, rumor detection, cyberspace security

中图分类号: