Abstract
Due to the concern for time and geological distance, the seeking health information behavior of patients has transferred from offline to online. The online information sharing has become one of the main sources where patients can obtain health information. Thus, the usefulness of online health information sharing is particularly important. This paper collects 9902 articles in health field from Baidu Experience which is the largest experience-sharing platform in China. It adopts the Information Adoption Model to analyze the impact of author’s credibility, text attributes, and pictures on the perceived usefulness of health-information-sharing articles. Results show that readers prefer long articles with more detailed health information and negative emotions in articles can affect readers’ perception of usefulness. And illustrated articles are easier to receive recognition. On the other hand, authors’ motivation in utilitarianism may lead to challenges to quality of the health-information-sharing article and, in return, hinder readers from adopt the information from the article.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yong, S.H., Kim, Y.G.: Why would online gamers share their innovation-conducive knowledge in the online game user community? Integrating individual motivations and social capital perspectives. Comput. Hum. Behav. 27(2), 956–970 (2011)
Hooff, B.V.D., Ridder, J.A.D.: Knowledge sharing in context: the influence of organizational commitment, communication climate and CMC use on knowledge sharing. J. Knowl. Manage. 8(6), 117–130 (2004)
China Association for Science and Technology: Chinese netizens’ demand for popular science search behavior report (first quarter of 2019), 26 April 2019/05 September 2019. http://www.cast.org.cn/art/2019/4/26/art_1281_94546.html
Kankanhalli, A., Tan, B.C.Y., Wei, K.K.: Contributing knowledge to electronic knowledge repositories: an empirical investigation. MIS Q. 29(1), 113–143 (2005)
Ma, M., Agarwal, R.: Through a glass darkly: information technology design, identity verification, and knowledge contribution in online communities. Inf. Syst. Res. 18(1), 42–67 (2007)
Galunic, D.C., Rodan, S.: Resource recombinations in the firm: knowledge structures and the potential for schumpeterian innovation. Strateg. Manag. J. 19(12), 1193–1201 (2015)
Sussman, S.W., Siegal, W.S.: Informational influence in organizations: an integrated approach to knowledge adoption. Inf. Syst. Res. 14(1), 47–65 (2003)
Parboteeah, D.V., Valacich, J.S., Wells, J.D.: The influence of website characteristics on a consumer’s urge to buy impulsively. Inf. Syst. Res. 20(1), 60–78 (2009)
Hwang, K.O., et al.: Social support in an Internet weight loss community. Int. J. Med. Informatics 79(1), 5–13 (2010)
Krishnamoorthy, S.: Linguistic features for review helpfulness prediction. Expert Syst. Appl. 42(7), 3751–3759 (2015)
Yoo, J., Kim, M.: The effects of online product presentation on consumer responses: a mental imagery perspective. J. Bus. Res. 67(11), 2464–2472 (2014)
Allen, W.: The influence of source credibility on communication effectiveness. Audiov. Commun. Rev. 1(2), 142–143 (1953)
Acknowledgments
This research is supported by the National Natural Science Foundation of China (No.71573197).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Gao, J., Xiao, Z., Cai, J., Wang, C., Wu, J. (2019). Perceived Usefulness of Online Health Information Sharing: A Text Mining Based Empirical Research. In: Chen, H., Zeng, D., Yan, X., Xing, C. (eds) Smart Health. ICSH 2019. Lecture Notes in Computer Science(), vol 11924. Springer, Cham. https://doi.org/10.1007/978-3-030-34482-5_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-34482-5_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34481-8
Online ISBN: 978-3-030-34482-5
eBook Packages: Computer ScienceComputer Science (R0)