Article ID Journal Published Year Pages File Type
6836065 Computers in Human Behavior 2018 30 Pages PDF
Abstract
This study investigates factors that affect user decisions on which information to share, and specifically whether and how to disclose sensitive personal information, when using social networking sites (SNSs). The determinants of personal information disclosure (self-disclosure) are identified using a framework that combines communication privacy management and social penetration theories. Communication privacy management theory is applied to identify which rules guide users' sharing of personal information. Social penetration theory is used to understand personal information disclosure approaches-deep and shallow-that people employ on SNSs. Structural equation modeling was used to analyze data from 315 Facebook users who were also undergraduate students. Results show that individuals self-disclose more on SNSs when they know how to coordinate disclosure boundaries, and particularly when they have learned from prior privacy infringements. While types of relationships are important in determining self-disclosure approaches, SNSs users who have experienced a privacy breach follow different privacy coordination rules compared with those who have not experienced such an incident. Our results present an interesting twist in which the “fooled once” users show higher levels of information sharing at all levels. These users have learned their lessons and their way through privacy management options, eventually leading to a higher self-disclosure.
Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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