Extracting the diffusion dynamics of crisis information on online social networks: Model and application

被引:5
作者
Chen, Anying [1 ,2 ]
Liu, Huan [3 ]
Su, Guofeng [4 ]
机构
[1] Jinan Univ, Sch Publ Adm & Emergency Management, Guangzhou 510632, Peoples R China
[2] Jinan Univ, Inst Publ Policy Res, Guangzhou 510632, Peoples R China
[3] Kyoto Univ, Disaster Prevent Res Inst, Kyoto 6110011, Japan
[4] Tsinghua Univ, Inst Publ Safety Res, Dept Engn Phys, Beijing 100084, Peoples R China
关键词
Crisis information; Diffusion dynamics; Population dynamics; Online social network; Parameter analysis;
D O I
10.1016/j.ijdrr.2023.104226
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Disaster mitigation greatly benefits from the diffusion of crisis information. To learn about the diffusion dynamics of crisis information on online social networks, this paper puts forward a crisis information diffusion model based on population dynamics and further analyses its parameters, such as ordinary users' average number of followers, the number of potential audience members who might spread the crisis information, the forwarding probability for each audience member and the attenuation speed of the information based on real data from Sina Weibo. In addition, a method for the prediction of crisis information diffusion is proposed and verified on the basis of this model. The results show that this model could describe and predict well the diffusion process of crisis information on online social networks, enabling relevant departments to develop appropriate strategies for crisis information diffusion.
引用
收藏
页数:13
相关论文
共 25 条
[1]   How Audiences Seek Out Crisis Information: Exploring the Social-Mediated Crisis Communication Model [J].
Austin, Lucinda ;
Liu, Brooke Fisher ;
Jin, Yan .
JOURNAL OF APPLIED COMMUNICATION RESEARCH, 2012, 40 (02) :188-207
[2]   Model of warning information diffusion on online social networks based on population dynamics [J].
Chen, Anying ;
Ni, Xiaoyong ;
Zhu, Haoran ;
Su, Guofeng .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2021, 567
[3]  
Comarela G., 2012, Proceedings of the 23rd ACM conference on Hypertext and social media, P123
[4]   Robust dynamic classes revealed by measuring the response function of a social system [J].
Crane, Riley ;
Sornette, Didier .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2008, 105 (41) :15649-15653
[5]   Crowd or Hubs: information diffusion patterns in online social networks in disasters [J].
Fan, Chao ;
Jiang, Yucheng ;
Yang, Yang ;
Zhang, Cheng ;
Mostafavi, Ali .
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2020, 46
[6]  
Feng Wang, 2012, Proceedings of the 2012 32nd International Conference on Distributed Computing Systems Workshops (ICDCS Workshops), P133, DOI 10.1109/ICDCSW.2012.16
[7]  
Fokas N., 2007, Rev. Sociol., V13, P5, DOI DOI 10.1556/REVSOC.14.2008.1
[8]   Modeling and Predicting Retweeting Dynamics on Microblogging Platforms [J].
Gao, Shuai ;
Ma, Jun ;
Chen, Zhumin .
WSDM'15: PROCEEDINGS OF THE EIGHTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING, 2015, :107-116
[9]   Talk of the network: A complex systems look at the underlying process of word-of-mouth [J].
Goldenberg, J ;
Libai, B ;
Muller, E .
MARKETING LETTERS, 2001, 12 (03) :211-223
[10]   Emergency information diffusion on online social media during storm Cindy in US [J].
Kim, Jooho ;
Bae, Juhee ;
Hastak, Makarand .
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2018, 40 :153-165