Disentangling social media influence in crises: Testing a four-factor model of social media influence with large data

被引:51
|
作者
Zhao, Xinyan [1 ]
Zhan, Mengqi [2 ]
Liu, Brooke F. [3 ]
机构
[1] Hong Kong Baptist Univ, Hong Kong, Hong Kong, Peoples R China
[2] Univ Texas Arlington, Arlington, TX 76019 USA
[3] Univ Maryland, College Pk, MD 20742 USA
关键词
Crisis communication; Social media influence; Measurement; Influencer; PUBLIC ENGAGEMENT; OPINION; POWER; NETWORKS; ORGANIZATIONS; LEADERSHIP; ONLINE;
D O I
10.1016/j.pubrev.2018.08.002
中图分类号
F [经济];
学科分类号
02 ;
摘要
Social media empower publics by providing a platform for their voices during crises. Digital enabled platforms allow individuals to become influentials by sharing their insights and expertise with others. Confronted with the fast-paced and complex dynamics of crises, we lack a systematic conceptualization and a valid measure of social media influence in the crisis context. By integrating diverse perspectives on influence, we propose a new framework that theorizes different dimensions of social media influence based on publics' communicative behaviors during crises. This integrated framework offers a refined conceptualization and measurement of social media influence in crises by incorporating the network perspective. We tested the framework with large-scale Twitter data from four crises. Results from multigroup CFA on Twitter influencers suggest that social media influence is composed of four factors: output, reactive outtake, proactive outtake, and network positioning. Each factor is associated with a distinct set of users' behavioral indicators (e.g., retweet). Implications for crisis communication and public relations are discussed.
引用
收藏
页码:549 / 561
页数:13
相关论文
共 50 条
  • [31] Social Media Influence and Electoral Competition
    Shmargad, Yotam
    Sanchez, Lisa
    SOCIAL SCIENCE COMPUTER REVIEW, 2022, 40 (01) : 4 - 23
  • [32] Events Influence Computation on Social Media
    Zhang Yu
    Yu Min
    He Yueying
    Zhao Zhonghua
    Qiao Yang
    Zhang Hua-Ping
    Shang Jianyun
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ELECTRONICS, NETWORK AND COMPUTER ENGINEERING (ICENCE 2016), 2016, 67 : 776 - 783
  • [33] Influence Value: Quantifying Topic Influence on Social Media
    Calderon, Fernando H.
    Chen, Yi-Shin
    2016 IEEE SECOND INTERNATIONAL CONFERENCE ON MULTIMEDIA BIG DATA (BIGMM), 2016, : 49 - 55
  • [34] A model for the influence of media on the ideology of content in online social networks
    Brooks, Heather Z.
    Porter, Mason A.
    PHYSICAL REVIEW RESEARCH, 2020, 2 (02):
  • [35] The Impact of Emotion: A Blended Model to Estimate Influence on Social Media
    Wei-Lun Chang
    Information Systems Frontiers, 2019, 21 : 1137 - 1151
  • [36] Effects of mass media and cultural drift in a model for social influence
    Mazzitello, Karina I.
    Candia, Julian
    Dossetti, Victor
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2007, 18 (09): : 1475 - 1482
  • [37] The Impact of Emotion: A Blended Model to Estimate Influence on Social Media
    Chang, Wei-Lun
    INFORMATION SYSTEMS FRONTIERS, 2019, 21 (05) : 1137 - 1151
  • [38] Effects of mass media action on the Axelrod model with social influence
    Rodriguez, Arezky H.
    Moreno, Y.
    PHYSICAL REVIEW E, 2010, 82 (02):
  • [39] Social Media Engagement Theory: Exploring the Influence of User Engagement on Social Media Usage
    Di Gangi, Paul M.
    Wasko, Molly
    JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING, 2016, 28 (02) : 53 - 73
  • [40] AUDIT TESTING OF PERSONAL DATA ON SOCIAL MEDIA
    Kupec, Vaclav
    Pisar, Premysl
    MARKETING IDENTITY: OFFLINE IS THE NEW ONLINE, 2019, : 155 - 170