Framing and measuring Multi-dimensional interpersonal privacy preferences of social networking site users

Abstract

In this paper, we focus on interpersonal boundary regulation as a means to balance the tradeoffs between engaging with others and protecting one’s privacy on social networking sites (SNSs). We examine boundary regulation from the combined perspectives of SNS design and end user behavior; we conduct a feature-oriented domain analysis of five popular SNS interfaces and 21 semi-structured SNS user interviews. We use this information to construct a taxonomy of 10 types of interpersonal boundaries SNS users regulate to manage their privacy preferences. We then develop and validate scales to operationalize these 10 boundary types to measure the multi-dimensional nature of SNS users’ privacy preferences by using a sample of 581 Facebook users. Our taxonomy provides a theoretical foundation for conceptualizing SNS user privacy, and our scales provide a more robust way to measure SNS users’ multi-faceted privacy preferences.