In the context of a myriad of mobile apps which collect personally identifiable information (PII) and a prospective market place of personal data, we investigate a user-centric monetary valuation of mobile PII. During a 6-week long user study in a living lab deployment with 60 participants, we collected their daily valuations of 4 categories of mobile PII (communication, e.g. phonecalls made received, applications, e.g. time spent on different apps, location and media, e.g. photos taken) at three levels of complexity (individual data points, aggregated statistics and processed, i.e. meaningful interpretations of the data). In order to obtain honest valuations, we employ a reverse second price auction mechanism. Our findings show that the most sensitive and valued category of personal information is location. We report statistically significant associations between actual mobile usage, personal dispositions, and bidding behavior. Finally, we outline key implications for the design of mobile services and future markets of personal data.
Studies have shown a connection between the individual personality of the user and the way he or she behaves on line. Today many millions of people around the world are connected by being members of various Internet social networks. (2009) studied the connection between the personality of the individual users and their behavior on a social network. They based their study on the self-reports of users of Facebook, one of the most popular social networks, and measured five personality factors using the NEO-PI-R (Costa & McCrae, 1992) questionnaire. They found that while there was a connection between the personalities of surfers and their behavior on Facebook, it was not strong. This study is based on that of (2009), but in our study the self-reports of subjects, were replaced by more objective criteria, measurements of the user-information upload on Facebook. A strong connection was found between personality and Facebook behavior. Implications of the results are discussed. We study the relationship between Facebook popularity (number of contacts) and personality traits on a large number of subjects. We test to which extent two prevalent viewpoints hold. That is, popular users (those with many social contacts) are the ones whose personality traits either predict many offline (real world) friends or predict propensity to maintain superficial relationships. We find that the predictor for number of friends in the real world (Extraversion) is also a predictor for number of Facebook contacts. We then test whether people who have many social contacts on Facebook are the ones who are able to adapt themselves to new forms of communication, present themselves in likable ways, and have propensity to maintain superficial relationships. We show that there is no statistical evidence to support such a conjecture. For more than a century, concern for privacy (CFP) has co-evolved with advances in information technology. The CFP refers to the anxious sense of interest that a person has because of various types of threats to the person's state of being free from intrusion. Research studies have validated this concept and identified its consequences. For example, research has shown that the CFP can have a negative influence on the adoption of information technology; but little is known about factors likely to influence such concern. This paper attempts to fill that gap. Because privacy is said to be a part of a more general ‘right to one's personality’, we consider the so-called ‘Big Five’ personality traits (agreeableness, extraversion, emotional stability, openness to experience, and conscientiousness) as factors that can influence privacy concerns. Protection motivation theory helps us to explain this influence in the context of an emerging pervasive technology: location-based services. Using a survey-based approach, we find that agreeableness, conscientiousness, and openness to experience each affect the CFP. These results have implications for the adoption, the design, and the marketing of highly personalized new technologies.  Online communities of different types have become an important part of the daily internet life of many people within the last couple of years. Both research and business have shown interest in studying the possibilities and risks related to these relatively new phenomena. Frequently discussed aspects that are tightly bound to online communities are their implications and effects on privacy issues. Available literature has shown that users generally disclose very much (private) information on such communities, and different factors influencing this behaviour were identified and studied. However, the influence and predictive power of personality traits on information disclosure in online communities has not yet been the subject of analysis. In this paper we report the results of an online survey investigating the relations between personality traits (based on the Fife-Factor Model), usage patterns and information disclosure of participants in different types of online communities. Despite concerns raised about the disclosure of personal information on social network sites, research has demonstrated that users continue to disclose personal information. The present study employs surveys and interviews to examine the factors that influence university students to disclose personal information on Facebook. Moreover, we study the strategies students have developed to protect themselves against privacy threats. The results show that personal network size was positively associated with information revelation, no association was found between concern about unwanted audiences and information revelation and finally, students' Internet privacy concerns and information revelation were negatively associated. The privacy protection strategies employed most often were the exclusion of personal information, the use of private email messages, and altering the default privacy settings. Based on our findings, we propose a model of information revelation and draw conclusions for theories of identity expression. Privacy is the most often-cited criticism of ubiquitous computing, and may be the greatest barrier to its long-term success. However, developers currently have little support in designing software architectures and in creating interactions that are effective in helping end-users manage their privacy. To address this problem, we present Confab, a toolkit for facilitating the development of privacy-sensitive ubiquitous computing applications. The requirements for Confab were gathered through an analysis of privacy needs for both end-users and application developers. Confab provides basic support for building ubiquitous computing applications, providing a framework as well as several customizable privacy mechanisms. Confab also comes with extensions for managing location privacy. Combined, these features allow application developers and end-users to support a spectrum of trust levels and privacy needs.  The social networking site (SNS) acts as a gateway through which online networking connections are made possible. Therefore, a user must be willing to provide his or her information to the SNS in order for others to find and “befriend” him or her and vice versa. Results from an online survey was used to test a trust-risk model of information disclosure in which two dispositional factors (Internet privacy concern and locus of control) and one situational factor (salience of SNS in daily life) were hypothesized to influence perceived risk regarding SNSs in general and trust in a SNS in particular. All proposed hypotheses were found significant, suggesting that the dispositional and situational factors are potentially salient in the SNS context. Findings also suggest that perhaps providing completed categories of personal information may be more sensitive than individual pieces of information alone.