Abstract-Smart phones can collect and share Bluetooth co-location traces to identify ad hoc or semi-permanent social groups. This information, known to group members but otherwise unavailable, can be leveraged in applications and protocols, such as recommender systems or delay-tolerant forwarding in ad hoc networks, to enhance the user experience. Group discovery using Bluetooth co-location is practical because: (i) Bluetooth is embedded in nearly every phone and has low battery consumption, (ii) the short wireless transmission range can lead to good group identification accuracy, and (iii) privacy-conscious users are more likely to share co-location data than absolute location data. This paper proposes the Group Discovery using Co-location traces (GDC) algorithm, which leverages user meeting frequency and duration to accurately detect groups. GDC is validated on one month of data collected from 141 smart phones carried by students on our campus. Users rated GDC's groups 30% better than groups discovered using the K-Clique algorithm. Additionally, GDC lends itself more easily to a distributed implementation, which achieves similar results with the centralized version while improving user's privacy.
Abstract-This paper explores how online social networks and co-presence social networks complement each other to form global, fused social relations. We collected Bluetoothbased co-presence data from mobile phones and Facebook social data from a shared set of 104 students. For improved analysis accuracy, we created weighted social graphs based on meeting frequency and duration for co-presence data, and based on wall writing and photo tagging for Facebook data. By analyzing the overall structural properties, we show the two networks represent two different levels of social engagement which complement each other. By fusing them together, the average path length and network diameter is shortened, and consequently the social connectivity increases significantly. By quantifying the contribution of each social network to the fused network in terms of node degree, edge weight, and community overlap, we discovered that the co-presence network improves social connectivity, while the online network brings greater cohesiveness to social communities.
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