Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 694-704.doi: 10.11896/jsjkx.210900186

• Interdiscipline & Application • Previous Articles     Next Articles

Evolutionary Game Analysis of WeChat Health Information Quality Optimization Based on Prospect Theory

WANG Xian-fang, ZHANG Liang, ZHANG Ning   

  1. School of Business,Qingdao University,Qingdao,Shandong 266100,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:WANG Xian-fang,born in 1996,postgraduate.Her main research interests include information management and so on.
    ZHANG Liang,born in 1979,Ph.D,associate professor,postgraduate supervisor.His main research interests include information management.
  • Supported by:
    Natural Science Foundation of Shandong Province,China(ZR2018MG005).

Abstract: The quality of health information in WeChat varies from good to bad.Research on the evolutionary process of platform,official account and user behavioral decision-making,explore the key factors that prevent the official account from publi-shing false information,and provide a useful reference for optimizing the health ecological environment.By constructing a three-party game model,system equilibrium points and constraints are solved,then the influencing factors and optimal stable state of the system evolution are simulated and analyzed.Prospect theory is introduced to explore the influence of the subject's risk attitude and loss aversion on the optimal outcome.Simulation experiments show that the platform and users are more sensitive to risks than losses.Compared with the high cost of supervision,the platform pays more attention to the improvement of reputation.Compared with the misleading caused by false information,users focus on satisfying subjective needs.Official accounts are more sensitive to losses,and the sensitivity to platform penalties is greater than fan losses.When the initial willingness of the official account to release real information is low,although external factors such as platform punishment and media exposure can curb the spread of fake health information,the optimal system is difficult to achieve as soon as possible.

Key words: Evolutionary game, Health information, Prospect theory, Quality optimization, WeChat platform

CLC Number: 

  • G206
[1] LI Y L,ZHANG X,WANG S S.Health information quality in social media:an analysis based on the features of real and fake health information[J].Journal of the China Society for Scientific and Technical Information,2018,37(3):294-304.
[2] WU S W,WANG Y D,ZHENG X.The game of credibility:the source and narrative of false health information and corrective information[J].Global Media Journal,2019,6(3):73-91.
[3] CHUA A Y K,BANERJEE S.To share or not to share:the role of epistemic belief in online health rumors[J].International Journal of Medical Informatics,2017(108):36-41.
[4] ZHANG Y,SUN Y,XIE B.Quality of health information forconsumers on the web:a systematic review of indicators,criteria,tools,and evaluation results[J].Journal of the Association for Information Science and Technology,2015,66(10):2071-2084.
[5] GAN C.Understanding WeChat users' liking behavior:An empirical study in China[J].Computers in Human Behavior,2017,68(1):30-39.
[6] SUSSMAN S W,SIEGAL W S.Informational influence in organizations:an integrated approach to knowledge adoption[J].Information Systems Research,2003,14(1):47-65.
[7] SUN Z M,WANG Z B.Research on Weibo health informationadoption based on information features[J].Information Theory and Practice,2019,42(3):146-152.
[8] HAN S X,ZENG Y L.Research on the influencing factors ofthe willingness to adopt health information on the WeChat public platform of digital youth under the background of public health emergencies[J].Library Science Research,2021(6):83-92.
[9] WANG W.Research on the health information adoption beha-vior of elderly WeChat users[J].International Press,2020,42(3):91-107.
[10] JIN J H,YAN X B,LI Y J,et al.How users adopt healthcare information:An empirical study of an online Q&A community[J].International Journal of Medical Informatics,2015(86):91-103.
[11] TANG X L,ZHANG B,ZHANG Y.Research on the willingness of online health community users to adopt information-Based on the perspective of health literacy and trust[J].Journal of Information Resources Management,2018,8(3):102-112.
[12] SUN Z M,HUA W N,WANG Z B.Research on health information adoption prediction of WeChat official accounts-based on information features and support vector machines[J].Information Theory and Practice,2018,41(7):72-77.
[13] LI Y,WANG X,LIN X,et al.Seeking and sharing health information on social media:A net valence model and cross-cultural comparison[J].Technological Forecasting and Social Change,2018,126:18-40.
[14] DENG Z,LIU S.Understanding consumer health information-seeking behavior from the perspective of the risk perception attitude framework and social support in mobile social media websites[J].International Journal of Medical Informatics,2017,105:98-109.
[15] ZHANG K.Research on the formation mechanism and conceptual model of WeChat Moments users' health information forwarding behavior[J].Library Magazine,2020,39(6):97-104.
[16] KUANG W B,WU X L.Research on evaluation index system of health communication effect based on WeChat official account[J].International Press,2019,41(1):153-176.
[17] HOU X R,FU Y,CHEN J.Research on user perception andutility of health information based on WeChat platform[J].Mo-dern Intelligence,2016,36(10):89-93.
[18] WANG W T,LIU Y S,YU X F,et al.A rooted analysis of the willingness to accept health information of middle-aged and elderly users based on the WeChat platform[J].Modern Intelligence,2020,40(1):69-78.
[19] SHANG L L,WANG T.Research on WeChat health information attention based on user information behavior[J].Information Science,2019,37(8):132-138
[20] JIN Y,ZHANG Q Y.Research on influencing factors of attention of health WeChat official accounts based on grounded theory[J].Library Theory and Practice,2018(4):48-52.
[21] YANG G,WEN J Y.Error correction of false health information in WeChat moments:Research on the impact of platforms,stra-tegies and issues[J].Journalism and Communication Studies,2020,27(8):26-43,126.
[22] ZHAP D X.Research on the optimization of information service quality of online health community-Based on the analysis of evolutionary game[J].Information Science,2018,36(8):149-154.
[23] GAN C.Understanding WeChat users' liking behavior:An empirical study in China[J].Computers in Human Behavior,2017,68(1):30-39.
[24] QU N W,XIA Z J,WANG Y M.Research on the rumor refutation effect of social media based on user information behavior[J].Information Science,2021,39(1):111-119.
[25] LI Z,CHEN L,BAI Y,et al.On diffusion-restricted social network:A measurement study of wechat moments[J].arXiv:1602.00193.
[26] XIONG Y,WEI Z H,LI C Q.Media exposure and IPO issuance review:effect and influencing mechanism[J].Economic Mana-gement,2020,42(11):141-159.
[27] FEI W,PAN Y N.The evolutionary game of food safety be-tween self-media,regulatory agencies and enterprises[J].Journal of South China Agricultural University,2020,19(6):84-100.
[28] ZHENG L.Game analysis of public opinion information quality evolution based on participatory governance theory[J].Information Science,2020,38(5):154-160,168.
[29] LI Y L,ZHANG X.Research on college students' social media health information discrimination ability[J].Library and Information Knowledge,2018(1):66-77,43.
[30] ZHANG D Y,KONG H X,XU L,et al.Research on the time characteristics of data-driven WeChat user information behavior[J].Library and Information Work,2019,63(20):104-111.
[31] HUANG S W,YU X G.Evolutionary game analysis of IPO information disclosure and supervision[J/OL].Management Science of China:1-8.[2021-05-07].https://doi.org/10.16381/j.cnki.issn1003-207x.2019.1325.
[32] FRIEDMAN D.Evolutionary games in economics[J].Econometrica:Journal of the Econometric Society,1991,59(3):637-666.
[33] TVERSKY A,KAHNEMAN D.Advances in prospect theory:Cumulative representation of uncertainty[J].Journal of Risk and Uncertainty,1992,5(4):297-323.
[34] ZHANG J H,CHEN F J,ZHANG J X.Three-Party evolu-tionary game analysis of online rumor supervision based on prospect theory[J].Information Science,2018,36(10):84-88.
[35] ZHANG W D,LI S T,LIANG E P.Research on the follow behavior of social media users based on the complete information game model[J].Information Science,2019,37(8):114-119.
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