A mapping of the factors related to self-disclosure on social network sites. (25th November 2021)

• Record Type: Journal Article
• Authors: Kanté, Mahamadou
• Is Part Of: International journal of big data management. Volume 2:Number 1(2022)
• Page Start: 60
• Page End: 69
• Publication Date: 2021-11-25
• Subjects: big data -- privacy paradox -- self-disclosure -- social network services -- SNSs -- social network sites; Big data -- Periodicals; Information resources management -- Periodicals; 658.4038
• Languages: English
• ISSNs: 2631-8679

Abstract

Privacy is a critical concern in the big data era. Users share their personal data to informal communities such as social media. Despite the evident benefits of social network sites and users concerns about privacy, people disclose personal information. Albeit users know the conceivable risks of sharing personal information, more users are doing so. It is important to identify the factors affecting self-disclosure on social network sites. In this paper, the audience is informed about these factors. Using a systematic approach, models/theories used in self-disclosure researches on social network sites were identified. It was observed that the convenience of building and maintaining relationships, social ties and norms, and expected outcomes are positively affecting while privacy concerns are negatively affecting. It was also found that the level of trust, perceived control and perceived similarity can affect online behaviour towards self-disclosure. The paper closes by proposing future line of inquiries.