TY - GEN
T1 - Supporting opportunities for context-aware social matching
T2 - 34th Annual Conference on Human Factors in Computing Systems, CHI 2016
AU - Mayer, Julia M.
AU - Hiltz, Starr Roxanne
AU - Barkhuus, Louise
AU - Väänänen, Kaisa
AU - Jones, Quentin
PY - 2016/5/7
Y1 - 2016/5/7
N2 - 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.
AB - 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.
KW - Context-aware computing
KW - Experience Sampling
KW - Opportunistic social matching
KW - Social recommender systems
UR - http://www.scopus.com/inward/record.url?scp=85014741876&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85014741876&partnerID=8YFLogxK
U2 - 10.1145/2858036.2858175
DO - 10.1145/2858036.2858175
M3 - Conference contribution
AN - SCOPUS:85014741876
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 2430
EP - 2441
BT - CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 7 May 2016 through 12 May 2016
ER -