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FriendSensing: recommending friends using mobile phones

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ACM Conference On Recommender Systems archive
Proceedings of the third ACM conference on Recommender systems table of contents

New York, New York, USA

SESSION: Short papers table of contents

Pages 273-276

Year of Publication: 2009

ISBN:978-1-60558-435-5

Authors

Daniele Quercia	MIT SENSEable City Laboratory, Cambridge, MA, USA
Licia Capra	University College London, London, United Kingdom

Sponsor

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 17, Downloads (12 Months): 17, Citation Count: 0

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ABSTRACT

We propose FriendSensing, a framework that automatically suggests friends to mobile social-networking users. Using short-range technologies (e.g., Bluetooth) on her mobile phone, a social-networking user "senses" and keeps track of other phones in her proximity. FriendSensing processes proximity records using a variety of algorithms that are based on social network theories of geographical proximity and of link prediction. It then returns a personalized and automatically generated list of people the user may know. We evaluate the extent to which FriendSensing helps users find people they know against real mobility and social network data.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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