Supporting Opportunities for Context-Aware Social Matching: An Experience Sampling Study

Julia Mayer; Starr Roxanne Hiltz; Louise Barkhuus; Kaisa Väänänen; Quentin Jones

doi:10.1145/2858036.2858175

Supporting Opportunities for Context-Aware Social Matching: An Experience Sampling Study

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

23 Citations (Scopus)

11 Downloads (Pure)

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 language	English
Title of host publication	Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
Place of Publication	New York
Publisher	ACM
Pages	2430-2441
Number of pages	12
ISBN (Electronic)	978-1-4503-3362-7
DOIs	https://doi.org/10.1145/2858036.2858175
Publication status	Published - 2016
Publication type	A4 Article in conference proceedings
Event	ACM SIGCHI Annual Conference on Human Factors in Computing Systems - Duration: 1 Jan 1900 → …

Conference

Conference	ACM SIGCHI Annual Conference on Human Factors in Computing Systems
Period	1/01/00 → …

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10.1145/2858036.2858175

Supporting Opportunities for Context-Aware 2016
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Accepted author manuscript, 2.12 MB

http://urn.fi/URN:NBN:fi:tuni-202009096929

Cite this

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title = "Supporting Opportunities for Context-Aware Social Matching: An Experience Sampling Study",

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.",

author = "Julia Mayer and Hiltz, {Starr Roxanne} and Louise Barkhuus and Kaisa V{\"a}{\"a}n{\"a}nen and Quentin Jones",

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language = "English",

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booktitle = "Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems",

publisher = "ACM",

note = "ACM SIGCHI Annual Conference on Human Factors in Computing Systems ; Conference date: 01-01-1900",

}

Mayer, J, Hiltz, SR, Barkhuus, L, Väänänen, K & Jones, Q 2016, Supporting Opportunities for Context-Aware Social Matching: An Experience Sampling Study. in Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, New York, pp. 2430-2441, ACM SIGCHI Annual Conference on Human Factors in Computing Systems, 1/01/00. https://doi.org/10.1145/2858036.2858175

Supporting Opportunities for Context-Aware Social Matching: An Experience Sampling Study. / Mayer, Julia; Hiltz, Starr Roxanne; Barkhuus, Louise et al.

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. New York : ACM, 2016. p. 2430-2441.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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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.

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T2 - ACM SIGCHI Annual Conference on Human Factors in Computing Systems

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Supporting Opportunities for Context-Aware Social Matching: An Experience Sampling Study

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