An empirical analysis of users privacy disclosure behaviors on social network sites
Users privacy on social network sites is one of the most important and urgent issues in both industry and academic fields. This paper is intended to investigate the effect of users demographics, social network site experience, personal social network size, and blogging productivity on privacy disclosure behaviors by analyzing the data collected from social network sites. Based on two levels of disclosed privacy sensitivity information, the textual information of a user's blog postings can be converted into a 4-tuple to represent their privacy disclosure patterns, containing the breadth and depth of disclosure, and frequencies of highly and less sensitive disclosures. Collections of a user's privacy disclosure patterns in social network sites can effectively reflect the user's privacy disclosure behaviors. Applying the general linear modeling approach to blogging data converted with a coding scheme, we find that males and females have significantly differentiated privacy disclosure patterns in dimensions related to the breadth and depth of disclosure. In addition, age has a significant negative relationship with the breadth and depth of disclosure, as well as with highly sensitive disclosure. We also find that social network site experience, personal social network size, and blog length are not significantly related to users privacy disclosure patterns, while blog number always has positive associations with privacy disclosure patterns.
privacy disclosure social network sites generalized linear model social media