Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data

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, 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.Comment: 15 pages, 2 figures. To appear in ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp 2014

Friends don't lie: inferring personality traits from social network structure

In this work, we investigate the relationships between social network structure and personality; we assess the performances of different subsets of structural network features, and in particular those concerned with ego-networks, in predicting the Big-5 personality traits. In addition to traditional survey-based data, this work focuses on social networks derived from real-life data gathered through smartphones. Besides showing that the latter are superior to the former for the task at hand, our results provide a fine-grained analysis of the contribution the various feature sets are able to provide to personality classification, along with an assessment of the relative merits of the various networks exploited.European Commission (PERSI Project within the Marie Curie COFUND-FP7)Italy. Ministero dell'istruzione, dell'università e della ricerca (FIRB S-PATTERNS project

Capturing personality from Facebook photos and photo-related activities: How much exposure do you need?

Photo-related activities are noticeably prevalent among social media users. On Facebook, users predominantly communicate visually and manage their self-presentation. Such online behaviours tend to mimic what would be expected of individuals’ offline personalities. This study sought to address the link between Facebook users’ photo-related activities and the Big Five personality traits by encoding basic Facebook visual features. Content analysis on the actual profiles (n = 115) and multiple regression analyses revealed many associations as a manifestation of users’ characteristics. For instance, Neuroticism and Extraversion predicted more photo uploads. Conscientiousness was predictive of more self-generated albums and video uploads and Agreeableness predicted the average number of received ‘likes’ and ‘comments’ on profile pictures. Additionally, the Facebook experience in interaction with the personality factors was found to be influential on the type of photo-related activity and the level of photo participation of users. The findings provide evidence that Facebook users with various personality traits set up albums and upload photos differently. Given the uses and gratification model, users adapt the construction of their profiles and manage their interactions to gratify their psychological needs on Facebook

Embeddedness and sequentiality in social media

Over the last decade, there has been an explosion of work around social media within CSCW. A range of perspectives have been applied to the use of social media, which we characterise as aggregate, actor-focussed or a combination. We outline the opportunities for a perspective informed by ethnomethodology and conversation analysis (EMCA)—an orientation that has been influential within CSCW, yet has only rarely been applied to social media use. EMCA approaches can complement existing perspectives through articulating how social media is embedded in the everyday lives of its users and how sequentiality of social media use organises this embeddedness. We draw on a corpus of screen and ambient audio recordings of mobile device use to show how EMCA research is generative for understanding social media through concepts such as adjacency pairs, sequential context, turn allocation / speaker selection, and repair