Connecting people through physical proximity and physical resources at a conference

  • Authors:

  • Alvin Chin;Bin Xu;Hao Wang;Lele Chang;Hao Wang;Lijun Zhu

  • Affiliations:

  • Nokia Research Center, Beijing;Nokia Research Center, Beijing;Nokia Research Center, Beijing;Nokia Research Center, Beijing;Nokia Research Center, Beijing;Tsinghua University, Beijing

  • Venue:
  • ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
  • Year:
  • 2013

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Abstract

This work investigates how to bridge the gap between offline and online behaviors at a conference and how the physical resources in the conference (the physical objects used in the conference for gathering attendees together in engaging an activity such as rooms, sessions, and papers) can be used to help facilitate social networking. We build Find and Connect, a system that integrates offline activities and interactions captured in real time with online connections in a conference environment, to provide a list of potential people one should connect to for forming an ephemeral social network. We investigate how social connections can be established and integrated with physical resources through positioning technology, and the relationship between physical proximity encounters and online social connections. Results from our two datasets of two trials, one at the UIC/ATC 2010 conference and GCJK internal marketing event, show that social connections that are reciprocal in relationship, such as friendship and exchanged contacts, have tighter, denser, and highly clustered networks compared to unidirectional relationships such as follow. We discover that there is a positive relationship between physical proximity encounters and online social connections before the social connection is made for friends, but a negative relationship for after the social connection is made. The first indicates social selection is strong, and the second indicates social influence is weak. Even though our dataset is sparse, nonetheless we believe our work is promising and novel which is worthy of future research.