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Behav. Sci. 2018, 8(6), 58; https://doi.org/10.3390/bs8060058

Examining Self-Disclosure on Social Networking Sites: A Flow Theory and Privacy Perspective

1
Department of Management, Ghana Technology University College, Accra PMB 100, Ghana
2
Department of Marketing and Entrepreneurship, University of Ghana Business School, Accra LG78, Ghana
3
Department of Computer Science, Ho Technical University, Ho HP217, Ghana
4
Department of Finance and Accounting, Ghana Technology University College, Accra PMB 100, Ghana
5
Lagos Business School, Pan-Atlantic University, Lagos, Nigeria
*
Authors to whom correspondence should be addressed.
Received: 2 April 2018 / Revised: 26 May 2018 / Accepted: 4 June 2018 / Published: 6 June 2018
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Abstract

Social media and other web 2.0 tools have provided users with the platform to interact with and also disclose personal information to not only their friends and acquaintances but also relative strangers with unprecedented ease. This has enhanced the ability of people to share more about themselves, their families, and their friends through a variety of media including text, photo, and video, thus developing and sustaining social and business relationships. The purpose of the paper is to identify the factors that predict self-disclosure on social networking sites from the perspective of privacy and flow. Data was collected from 452 students in three leading universities in Ghana and analyzed with Partial Least Square-Structural Equation Modeling. Results from the study revealed that privacy risk was the most significant predictor. We also found privacy awareness, privacy concerns, and privacy invasion experience to be significant predictors of self-disclosure. Interaction and perceived control were found to have significant effect on self-disclosure. In all, the model accounted for 54.6 percent of the variance in self-disclosure. The implications and limitations of the current study are discussed, and directions for future research proposed. View Full-Text
Keywords: self-disclosure; social networking sites; flow; privacy concerns; structural equation modeling; Ghana self-disclosure; social networking sites; flow; privacy concerns; structural equation modeling; Ghana
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ampong, G.O.A.; Mensah, A.; Adu, A.S.Y.; Addae, J.A.; Omoregie, O.K.; Ofori, K.S. Examining Self-Disclosure on Social Networking Sites: A Flow Theory and Privacy Perspective. Behav. Sci. 2018, 8, 58.

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