Data privacy model for social media platforms

Abstract

Data Privacy on social media platforms such as Facebook, Twitter, and Google+ has become a vital research field because of the sharp growth in the number of users and the number of social media applications. In recent years, there has been an exponential increase in user generated text content, mainly in the terms of posts, tweets, reviews, and messages on social media. This increase in textual information creates many problems related to privacy. Data privacy is susceptible to personal behavior, due to the shared information structure medium of the social media platforms. This paper proposes a hyped model based on Communication Privacy Management Theory (CPM) and Theory of Planned Behavior (TPB) by using new privacy factors that affect the user's attitude.