An Empirical Investigation of Disclosure of Personal Information in Ubiquitous Social Computing

Abstract

Abstract-Privacy has already been identified as the main threat to long-term success of ubiquitous computing, especially in environments, which target at promoting ubiquitous social networking. Notably, these environments are founded on disclosure of personal information and thus, the amount of data disclosed is directly proportional to potential networking benefits. The networking advantages would be maximized by sharing all available personal data, however this would result in jeopardizing of users' privacy and a compromise is necessary. Consequently, privacy management systems of ubiquitous computing must be capable of disclosing only personal data, which is relevant, however not sensitive in specific circumstances. In this paper we provide insight into human personal data sensitivity and disclosure decisions by presenting results of an online survey regarding respondents' willingness to share their personal information under different circumstances. We believe that our findings provide relevant inputs for the design of management privacy models in ubiquitous computing.

MoodLight

“…This convergence of personal information and increasingly public display will require a more refined understanding of the dynamics of technology-mediated self-revelation and an appreciation of the risks of minimally controlled automated disclosure [21; 32]. …”

“…Based on ubiquitous computing investigations of the mechanics of automated disclosure [21; 32], we anticipated that there would be interesting tensions between the passive and automatic process of self-revelation provided by the sensing device and traditional practices of self-disclosure that are typically characterized by intentionality. In particular, we found through the process of designing the MoodLight system that our own understanding of the nature of these practices of revelation and disclosure were challenged.…”

“…While users largely remain in control of self-disclosure decisions on social media sites through the voluntary nature of posts, with sensor-based systems that can passively and continuously track personal information there are risks associated with automated disclosure [cf. 21; 32]. Managing disclosure in daily life “is an intuitive, situated social process” [21, p. 2] while managing disclosure in ubiquitous computing is complicated by the seamlessness with which these systems strive to operate.…”

The influential factors for the variation of data sensitivity in ubiquitous social networking

“…In previous studies, the identity of the inquirer was identified as the primary index for selection of data disclosure decisions in ubiquitous computing (Lederer et al, 2003;Davis and Gutwin, 2005;Olson et al, 2005;Jones et al, 2004;Consolvo et al, 2005). On the other hand, USN services advance the attention to other factors as crucial determinants for data disclosure, due to their primary focus on initiation of relationships between strangers (Sapuppo and Sørensen, 2011;Sapuppo and Seet, 2012). Several influential factors that impact personal data disclosure in USN, such as users' current activities and location familiarity, were identified during an empirical investigation, based on predefined data disclosure preferences (Sapuppo, 2012a).…”

Ubiquitous Social Networking: Concept and Evaluation

“…gender, age, favorite music, etc.). This categorization was already used in a previous investigation about disclosure of personal information in ubiquitous social computing environments and the detailed description of the provided data types can be found in (Sapuppo and Seet, 2012). Participants were aware that potential networking benefits would be directly proportional to the amount of shared information, thus their ad hoc data disclosure decisions were representing a compromise between privacy risks and potential networking benefits.…”