Supporting opportunities for context-aware social matching: An experience sampling study

Julia M. Mayer, Starr Roxanne Hiltz, Louise Barkhuus, Kaisa Väänänen, Quentin Jones

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

Mobile social matching systems aim to bring people together in the physical world by recommending people nearby to each other. Going beyond simple similarity and proximity matching mechanisms, we explore a proposed framework of relational, social and personal context as predictors of match opportunities to map out the design space of opportunistic social matching systems. We contribute insights gained from a study combining Experience Sampling Method (ESM) with 85 students of a U.S. university and interviews with 15 of these participants. A generalized linear mixed model analysis (n=1704) showed that personal context (mood and busyness) as well as sociability of others nearby are the strongest predictors of contextual match interest. Participant interviews suggest operationalizing relational context using social network rarity and discoverable rarity, and incorporating skill level and learning/teaching needs for activity partnering. Based on these findings we propose passive context-awareness for opportunistic social matching.

Original languageEnglish (US)
Title of host publicationCHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages2430-2441
Number of pages12
ISBN (Electronic)9781450333627
DOIs
StatePublished - May 7 2016
Event34th Annual Conference on Human Factors in Computing Systems, CHI 2016 - San Jose, United States
Duration: May 7 2016May 12 2016

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other34th Annual Conference on Human Factors in Computing Systems, CHI 2016
Country/TerritoryUnited States
CitySan Jose
Period5/7/165/12/16

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

Keywords

  • Context-aware computing
  • Experience Sampling
  • Opportunistic social matching
  • Social recommender systems

Fingerprint

Dive into the research topics of 'Supporting opportunities for context-aware social matching: An experience sampling study'. Together they form a unique fingerprint.

Cite this