31st Annual CHI Conference on Human Factors in Computing Systems: Changing Perspectives, CHI 2013, pp.3287 - 3296
Abstract
This study explores the links between motives for using a social network service and numerical measures of that activity. Specifically, it identified motives for Facebook use by employing a Uses and Gratifications (U&G) approach and then investigated the extent to which these motives can be predicted through usage and network metrics collected automatically via the Facebook API. In total, 11 Facebook usage metrics and eight personal network metrics served as predictors. Results showed that all three variable types in this expanded U&G frame of analysis (covering social antecedents, usage metrics, and personal network metrics) effectively predicted motives and highlighted interesting behaviors. To further illustrate the power of this framework, the intricate nature of privacy in social media was explored and relationships drawn between privacy attitudes (and acts) and measures of use and network structure.
Publisher
31st Annual CHI Conference on Human Factors in Computing Systems: Changing Perspectives, CHI 2013