Context-Aware Coproduction: Implications for Recommendation Algorithms

Jiawei Chen; Afsaneh Doryab; Benjamin Vincent Hanrahan; Alaaeddine Yousfi; Jordan Beck; Xiying Wang; Victoria Bellotti; Anind K. Dey; John Carroll

doi:10.1007/978-3-030-15742-5_54

Context-Aware Coproduction: Implications for Recommendation Algorithms

Jiawei Chen, Afsaneh Doryab, Benjamin Vincent Hanrahan, Alaaeddine Yousfi, Jordan Beck, Xiying Wang, Victoria Bellotti, Anind K. Dey, John Carroll

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Coproduction is an important form of service exchange in local community where members perform and receive services among each other on non-profit basis. Local coproduction systems enhance community connections and re-energize neighborhoods but face difficulties matching relevant and convenient transaction opportunities. Context-aware recommendations can provide promising solutions, but are so far limited to matching spatio-temporal and static user contexts. By analyzing data from a transportation-share app during a 3-week study with 23 participants, we extend the design scope for context-aware recommendation algorithms to include important community-based parameters such as sense of community. We find that inter- and intra-relationships between spatio-temporal and community-based social contexts significantly impact users’ motivation to request or provide service. The results provide novel insights for designing context-aware recommendation algorithms for community coproduction services.

Original language	English (US)
Title of host publication	Information in Contemporary Society - 14th International Conference, iConference 2019, Proceedings
Editors	Michelle H. Martin, Natalie Greene Taylor, Bonnie Nardi, Caitlin Christian-Lamb
Publisher	Springer Verlag
Pages	565-577
Number of pages	13
ISBN (Print)	9783030157418
DOIs	https://doi.org/10.1007/978-3-030-15742-5_54
State	Published - Jan 1 2019
Event	14th International Conference on Information in Contemporary Society, iConference 2019 - Washington, United States Duration: Mar 31 2019 → Apr 3 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11420 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th International Conference on Information in Contemporary Society, iConference 2019
Country	United States
City	Washington
Period	3/31/19 → 4/3/19

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All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Cite this

Chen, J., Doryab, A., Hanrahan, B. V., Yousfi, A., Beck, J., Wang, X., Bellotti, V., Dey, A. K., & Carroll, J. (2019). Context-Aware Coproduction: Implications for Recommendation Algorithms. In M. H. Martin, N. G. Taylor, B. Nardi, & C. Christian-Lamb (Eds.), Information in Contemporary Society - 14th International Conference, iConference 2019, Proceedings (pp. 565-577). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11420 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-15742-5_54

Chen, Jiawei ; Doryab, Afsaneh ; Hanrahan, Benjamin Vincent ; Yousfi, Alaaeddine ; Beck, Jordan ; Wang, Xiying ; Bellotti, Victoria ; Dey, Anind K. ; Carroll, John. / Context-Aware Coproduction : Implications for Recommendation Algorithms. Information in Contemporary Society - 14th International Conference, iConference 2019, Proceedings. editor / Michelle H. Martin ; Natalie Greene Taylor ; Bonnie Nardi ; Caitlin Christian-Lamb. Springer Verlag, 2019. pp. 565-577 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Coproduction is an important form of service exchange in local community where members perform and receive services among each other on non-profit basis. Local coproduction systems enhance community connections and re-energize neighborhoods but face difficulties matching relevant and convenient transaction opportunities. Context-aware recommendations can provide promising solutions, but are so far limited to matching spatio-temporal and static user contexts. By analyzing data from a transportation-share app during a 3-week study with 23 participants, we extend the design scope for context-aware recommendation algorithms to include important community-based parameters such as sense of community. We find that inter- and intra-relationships between spatio-temporal and community-based social contexts significantly impact users{\textquoteright} motivation to request or provide service. The results provide novel insights for designing context-aware recommendation algorithms for community coproduction services.",

author = "Jiawei Chen and Afsaneh Doryab and Hanrahan, {Benjamin Vincent} and Alaaeddine Yousfi and Jordan Beck and Xiying Wang and Victoria Bellotti and Dey, {Anind K.} and John Carroll",

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Chen, J, Doryab, A, Hanrahan, BV, Yousfi, A, Beck, J, Wang, X, Bellotti, V, Dey, AK & Carroll, J 2019, Context-Aware Coproduction: Implications for Recommendation Algorithms. in MH Martin, NG Taylor, B Nardi & C Christian-Lamb (eds), Information in Contemporary Society - 14th International Conference, iConference 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11420 LNCS, Springer Verlag, pp. 565-577, 14th International Conference on Information in Contemporary Society, iConference 2019, Washington, United States, 3/31/19. https://doi.org/10.1007/978-3-030-15742-5_54

Context-Aware Coproduction : Implications for Recommendation Algorithms. / Chen, Jiawei; Doryab, Afsaneh; Hanrahan, Benjamin Vincent; Yousfi, Alaaeddine; Beck, Jordan; Wang, Xiying; Bellotti, Victoria; Dey, Anind K.; Carroll, John.

Information in Contemporary Society - 14th International Conference, iConference 2019, Proceedings. ed. / Michelle H. Martin; Natalie Greene Taylor; Bonnie Nardi; Caitlin Christian-Lamb. Springer Verlag, 2019. p. 565-577 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11420 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Chen, Jiawei

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AU - Yousfi, Alaaeddine

AU - Beck, Jordan

AU - Wang, Xiying

AU - Bellotti, Victoria

AU - Dey, Anind K.

AU - Carroll, John

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AB - Coproduction is an important form of service exchange in local community where members perform and receive services among each other on non-profit basis. Local coproduction systems enhance community connections and re-energize neighborhoods but face difficulties matching relevant and convenient transaction opportunities. Context-aware recommendations can provide promising solutions, but are so far limited to matching spatio-temporal and static user contexts. By analyzing data from a transportation-share app during a 3-week study with 23 participants, we extend the design scope for context-aware recommendation algorithms to include important community-based parameters such as sense of community. We find that inter- and intra-relationships between spatio-temporal and community-based social contexts significantly impact users’ motivation to request or provide service. The results provide novel insights for designing context-aware recommendation algorithms for community coproduction services.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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PB - Springer Verlag

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ER -

Chen J, Doryab A, Hanrahan BV, Yousfi A, Beck J, Wang X et al. Context-Aware Coproduction: Implications for Recommendation Algorithms. In Martin MH, Taylor NG, Nardi B, Christian-Lamb C, editors, Information in Contemporary Society - 14th International Conference, iConference 2019, Proceedings. Springer Verlag. 2019. p. 565-577. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-15742-5_54

Access to Document

10.1007/978-3-030-15742-5_54