BS-3-29 Inferring social relations with smartphone proximity networks(BS-3. Advanced Networking Technologies for Innovative Information Networks)

• Tiantian Jiang

  Institute of Industrial Science, The University of Tokyo

• Ito Masaki

  Institute of Industrial Science, The University of Tokyo

• Sezaki Kaoru

  Institute of Industrial Science, The University of Tokyo

Abstract

A fundamental feature of social life is social interaction; people interact frequently with others in their daily life. Understanding a user's social interactions and relations in the physical world has shown its importance in building context-aware applications. While mobile phone has become one of essential parts of people's daily life, data collected from mobile phones have the potential to infer the relational dynamics of individuals. In this paper, using smartphone Wi-Fi Direct as a proximity sensor to create social networks, we present a probabilistic approach to mine human interaction types in real life. Our analysis is conducted on Wi-Fi data continuously sensed with smartphones that carried by a group of people who are professionally or personally related. Our goal is to discover different social activities such as chatting with friends from human-human interaction logs and then characterize them by the set of people involved, time and location of the occurring event.

Journal

• Proceedings of the IEICE General Conference

  Proceedings of the IEICE General Conference 2016 (2), "S-68"-"S-69", 2016-03-01

  The Institute of Electronics, Information and Communication Engineers

Details

• CRID: 1572261552388623616
• NII Article ID: 110010038496
• NII Book ID: AN10471452
• Text Lang: en
• Data Source:
  • CiNii Articles