A mapping of the factors related to self-disclosure on social network sites Online publication date: Sun, 05-Dec-2021
by Mahamadou Kanté
International Journal of Big Data Management (IJBDM), Vol. 2, No. 1, 2022
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Big Data Management (IJBDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook