PRIVACY IN ONLINE SOCIAL NETWORKS

Abstract

Debates about privacy issues on the social networking websites never stop. As social media becomes ubiquitous, better understanding about users' privacy in the context of online social networks is critical. However, the information privacy concern used by e-commerce research is not sufficient to capture the specificities of individuals' privacy concern under this new context. In this paper, we propose and empirically validate a new multi-dimensional privacy concept fit to the complex features of online social interactions. Further, we propose that role related constructs are critical source of privacy concern in online social networks. The four dimensions of privacy concern aggregate to form general privacy concern which predicts individual's risk belief. Data were collected on the Amazon Mechanical Turks platform. Empirical results support the validity of the proposed scale of the multi-dimensional privacy concern construct. We also find evidence that the different dimensions of privacy concern may be influenced differently by role related constructs (role overload and role conflict). © (2011) by the AIS/ICIS Administrative Office, All rights reserved.