Dimensionality of information disclosure behavior

In studies of people's privacy behavior, the extent of disclosure of personal information is typically measured as a summed total or a ratio of disclosure. In this paper, we evaluate three information disclosure datasets using a six-step statistical analysis, and show that people's disclosure behaviors are rather multidimensional: participants' disclosure of personal information breaks down into a number of distinct factors. Moreover, people can be classified along these dimensions into groups with different disclosure styles. This difference is not merely in degree, but rather also in kind: one group may for instance disclose location-related but not interest-related items, whereas another group may behave exactly the other way around. We also found other significant differences between these groups, in terms of privacy attitudes, behaviors, and demographic characteristics. These might for instance allow an online system to classify its users into their respective privacy group, and to adapt its privacy practices to the disclosure style of this group. We discuss how our results provide relevant insights for a more user-centric approach to privacy and, more generally, advance our understanding of online privacy behavior. (C) 2013 Elsevier Ltd. All rights reserved.