管理评论

管理评论 ›› 2024, Vol. 36 ›› Issue (3): 132-145.

• 电子商务与信息管理 • 上一篇    

“回音室”效应下社会化媒体不实信息传播的意见领袖群组识别与分析研究

江成1, 申洁2, 朱建明3   

  1. 1. 首都经济贸易大学管理工程学院, 北京 100070;
    2. 中国社会科学院大学法学院, 北京 102401;
    3. 中国科学院大学应急管理科学与工程学院, 北京 100049
  • 收稿日期:2021-07-16 发布日期:2024-04-24
  • 作者简介:江成，首都经济贸易大学管理工程学院副教授，硕士生导师，博士;申洁，中国社会科学院大学法学院讲师，硕士;朱建明（通讯作者），中国科学院大学应急管理科学与工程学院教授，博士。
  • 基金资助:
    国家自然科学基金青年项目(72004143);国家自然科学基金面上项目(71272189);北京市属高等学校优秀青年人才培育计划项目(BPHR202203164)。

Research on the Identification and Analysis of Opinion Leader Groups in the UnconfirmedInformation Propagation under the Echo Chamber Effect in Social Media

Jiang Cheng1, Shen Jie2, Zhu Jianming3   

  1. 1. School of Management Engineering, Capital University of Economics and Business, Beijing 100070;
    2. School of Law, University of Chinese Academy of Social Sciences, Beijing 102401;
    3. School of Emergency Management Science and Engineering, University of Chinese Academy of Sciences, Beijing 100049
  • Received:2021-07-16 Published:2024-04-24

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摘要： 不实信息具有传播速度快、范围广和衍生话题多的特性,是信息管理领域重要研究课题之一,而"回音室"效应使得社会化媒体中不实信息的传播复杂性急剧增加,给管理决策带来全新挑战。因此,从"回音室"效应视角探究社会化媒体不实信息传播的机理和干预策略,对于推进社会治理现代化意义重大。本文以新冠疫情期间微博平台"双黄连事件"传播数据集为例,开展实验分析。首先,利用复杂网络理论构建用户转发关系网络,并运用聚类模型和设计指标分析该网络信息传播过程中的"回音室"效应。其次,探究不实信息传播过程中的话题引爆点,构建基于"回音室"浅层传播和深层传播的意见领袖识别模型。再次,通过"双黄连事件"多个平台传播数据集和其他不实信息传播数据集验证意见领袖识别模型的准确性。最后,从政府机构、企业平台和平台用户多角度提出不实信息治理的政策建议,以期帮助决策者更快更好地管控不实信息的传播。

关键词: 社会化媒体, 不实信息, “回音室”效应, 意见领袖, 传播机理

Abstract: Unconfirmed information is one of the most important research topics in the field of crisis management, because of its fast, wide and derivative dissemination. The “echo chamber” effect in social media sharply increases the complexity of propagation of unconfirmed information, bringing new challenges to management decision-making. Therefore, exploring the propagation mechanism and intervention strategies of unconfirmed information in social media is significant to social governance and policy making. This paper takes the “Shuanghuanglian incident” spread on the Weibo platform during the Covid-19 period as an example to carry out an experimental analysis. Firstly, we use complex network theories to build a micro network of user forwarding and propagation, and analyze the process of information propagation through clustering models and the designed indicators under the “echo chamber” effect. Secondly, we explore the topic tipping points in the propagation of unconfirmed information, and establish an opinion leader identification model based on the shallow and deep propagation of “echo chamber”. Thirdly, we validate the proposed model through various datasets of multiple platforms and some other unconfirmed information datasets. Finally, we propose unconfirmed information intervention strategies and policy recommendations from the perspectives of government agencies, enterprise platforms and platform users, in order to help decision makers to better manage and control the spread of unconfirmed information.

Key words: social media, unconfirmed information, echo chamber effect, opinion leader, propagation mechanism