Abstract
Technological advances are driving the growth of online health communities. However, there are some problems such as low user participation and insignificant social benefits in online health communities. This paper discusses the evolution law of information sharing behavior of members of online health community to study the influence of different behaviors on health information sharing results and explore the ways to improve the level of community information sharing. Based on BA scale-free network (Albert-László Barabás and Réka Albert scale-free network), this paper established an information sharing behavior model for members of online health community with the evolutionary game theory method, and discussed the influence of different game parameters and initial conditions on the evolution results of information sharing behavior of community patients with the method of numerical experiment. It is found that the key to improve the level of community information sharing is to improve the benefit of patients’ information sharing, the proportion of patients sharing information at the initial moment, and the degree of network nodes, and reduce the sharing cost. Community managers should improve the information conversion ability and information absorption ability of community patients through offline activities, professional guidance, and other forms. At the same time, it can reduce the difficulty and risk of information sharing and strengthen the connection among members, thus comprehensively enhancing the value of the community.
Similar content being viewed by others
Data availability
We can provide the data.
Abbreviations
- BA scale-free network:
-
Albert-László Barabás and Réka Albert scale-free network
- ICR:
-
initial collaborator ratio
References
Yan Z, Wang T, Chen Y, Zhang H (2016a) Knowledge sharing in online health communities: a social exchange theory perspective [J]. Inf Manag 53(5):643–653
Fox S (2011) The Social Life of Health Information 2011 [M]. Pew Internet & American Life Project Washington, Dc
Zhang X, Liu S, Deng Z, et al. (2017) Knowledge sharing motivations in online health communities: a comparative study of health professionals and normal users [J]. Comput Hum Behav. S0747563217303989.
Tao A-J (2010) To discuss the privacy protection of personal medical information [D]. Southwest University of Political Science and Law
Nonaka I (2015) The knowledge-creating company [M], The knowledge-creating company. Harvard Business Press, 175–187
Smith JM, Price GR (1973) The logic of animal conflict [J]. Nature 246(11):5–5
Meng F, Guo X, Peng Z, Zhang X, Vogel D (2019) The routine use of mobile health services in the presence of health consciousness [J]. Electron Commer Res Appl 35:100847
Wicks P, Keininger DL, Massagli MP, la Loge C, Brownstein C, Isojärvi J, Heywood J (2012) Perceived benefits of sharing health data between people with epilepsy on an online platform [J]. Epilepsy Behav 23(1):16–23
Oh S (2014) The characteristics and motivations of health answerers for sharing information, knowledge, and experiences in online environments [J]. J Assoc Inf Sci Technol 63(3):543–557
Krasnova H, Spiekermann S, Koroleva K, Hildebrand T (2010) Online social networks: why we disclose [J]. J Inf Technol 25(2):109–125
Perse EM, Ferguson DA (2000) The benefits and costs of web surfing [J]. Commun Q 48(4):343–359
Matthews P, Simon J (2012) Evaluating and enriching online knowledge exchange: a socio-epistemological perspective [M]//Virtual Communities, Social Networks and Collaboration
Zhang X, Chen X, Hou D-L et al (2016) An analysis of online health information disclosure willingness influencing factors: an integrated model of TPB and privacy calculus [J]. Inf Doc Serv 37(1):48–53
Escoffery C, Diiorio C, Yeager KA et al (2008) Use of computers and the internet for health information by patients with epilepsy [J]. Epilepsy Behav 12(1):109–114
Barabasi AL, Albert R (1999) Emergence of scaling in random networks [J]. Science 286(5439):509–512
Zhang J-Q (2015) Empirical research on information acquiring and information sharing intention and behavior in virtual communities [J]. Inf Sci 8:59–64
Vaala SE, Lee JM, Hood KK et al (2017) Sharing and helping: predictors of adolescents’ willingness to share diabetes personal health information with peers [J]. J Am Med Inform Assoc 25(2):135–141
Kreps D (2018) Notes on the theory of choice [M]. Routledge
Weibull JW (1997) Evolutionary game theory [M]. MIT press
Hauert C, Szabó G (2005) Game theory and physics [J]. Am J Phys 73(5):405–414
Simon SR, Evans JS, Benjamin A, Delano D, Bates DW (2009) Patients’ attitudes toward electronic health information exchange: qualitative study [J]. J Med Internet Res 11(3):e30
Huberman BA, Glance NS (1993) Evolutionary games and computer simulations.[J]. Proc Natl Acad Sci U S A 90(16):7716–7718
Funding
This study was partially funded by the National Natural Science Foundation of China (numbers 71971123 and 71571105).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Competing interests
The authors declare that they have no conflict of interest.
Ethical approval and consent to participate
Approved.
Consent for publication
Approved.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We confirm that the content of the manuscript has not been published or submitted for publication elsewhere.
Rights and permissions
About this article
Cite this article
Zhu, P., Shen, J. & Xu, M. Study on the evolution of information sharing strategy for users of online patient community. Pers Ubiquit Comput 27, 689–695 (2023). https://doi.org/10.1007/s00779-020-01464-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00779-020-01464-6