The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
Self-disclosure in social networking sites: The role of perceived cost, perceived benefits and social influence
Open accessAbstract
Purpose: – The purpose of this paper is to examine the relative impacts of perceived cost, perceived benefits, and social influence on self-disclosure behaviors in social networking sites under an integrated theoretical framework. Design/methodology/approach: – Building upon social exchange theory and privacy calculus theory, an integrated model was developed. The model was tested empirically using a sample of 405 social networking site’s users. Users were required to complete a survey regarding self-disclosure behaviors in Facebook. Findings: – The results indicate that social influence is the factor which exhibits the strongest effect on self-disclosure in social networking sites, followed by perceived benefits. Surprisingly, perceived privacy risk does not have any significant impact on self-disclosure. Research limitations/implications: – The results inform researchers about the importance to incorporate social influence factors and cultural factors into future online self-disclosure study. Practical implications: – The results suggest that users focus on the benefits as well as social influence when they decide to reveal personal information in social networking sites, but pay less attention to the potential privacy risks. Educators are advised to launch educational programs to raise students’ awareness to the potential risks of self-disclosure in social networking sites. Service providers of social networking sites are encouraged to provide intuitive privacy indices showing users the levels of privacy protection. Originality/value: – This paper is one of the first to develop and empirically tests an integrated model of self-disclosure in social networking sites.
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Cites
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Cited by
Inside out and outside in: How the COVID-19 pandemic affects self-disclosure on social media
Nabity-Grover, T., Cheung, C. M. K., & Thatcher, J. B. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102188 · Cited by 309
Self-citationWhy people participate in the sharing economy: an empirical investigation of Uber
Lee, Z. W. Y., Chan, T. K. H., Balaji, M. S., & Chong, A. Y.-L. (2018) · Internet Research · doi:10.1108/intr-01-2017-0037 · Cited by 305
Self-citationMousavi, R., Chen, R., Kim, D. J., & Chen, K. (2020) · Decision Support Systems · doi:10.1016/j.dss.2020.113323 · Cited by 156
Privacy Concerns and Self-Disclosure in Private and Public Uses of Social Media
Gruzd, A., & Hernández-García, Á. (2018) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2017.0709 · Cited by 97
Teck Soon, H., & Syed A. Kadir, S. L. (2017) · Internet Research · doi:10.1108/intr-08-2016-0256 · Cited by 53
Metadata
- Authors
- Cheung, C., Lee, Z. W. Y., & Chan, T. K. H.
- Venue
- Internet Research
- Publisher
- Emerald
- Published
- 2015-04-07
- Volume
- 25
- Issue
- 2
- Pages
- 279-299
- ISSN
- 1066-2243 (ISSN-L)
- OpenAlex
- W1507592641
- Cited by
- 270
- References
- 72
- FWCI
- 64.23
- Type
- journal article
- Language
- en
- Open access
- green
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.