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"the crowd keeps me in shape": social psychology and the present and future of health social machines

Published: 13 May 2013 Publication History

Abstract

Can the Web help people live healthier lives? This paper seeks to answer this question through an examination of sites, apps and online communities designed to help people improve their fitness, better manage their disease(s) and conditions, and to solve the often elusive connections between the symptoms they experience, diseases and treatments. These health social machines employ a combination of both simple and complex social and computational processes to provide such support. We first provide a descriptive classification of the kinds of machines currently available, and the support each class offers. We then describe the limitations exhibited by these systems and potential ways around them, towards the design of more effective machines in the future.

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Cited By

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  • (2020)Artificial intelligence and machine learning in dynamic cyber risk analytics at the edgeSN Applied Sciences10.1007/s42452-020-03559-42:11Online publication date: 6-Oct-2020
  • (2019)Privacy, Trust and Ethical IssuesThe Theory and Practice of Social Machines10.1007/978-3-030-10889-2_4(149-200)Online publication date: 15-Feb-2019
  • (2019)Characterising Social MachinesThe Theory and Practice of Social Machines10.1007/978-3-030-10889-2_1(1-41)Online publication date: 15-Feb-2019
  • Show More Cited By

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  1. "the crowd keeps me in shape": social psychology and the present and future of health social machines

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    Published In

    cover image ACM Other conferences
    WWW '13 Companion: Proceedings of the 22nd International Conference on World Wide Web
    May 2013
    1636 pages
    ISBN:9781450320382
    DOI:10.1145/2487788

    Sponsors

    • NICBR: Nucleo de Informatcao e Coordenacao do Ponto BR
    • CGIBR: Comite Gestor da Internet no Brazil

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 May 2013

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    Author Tags

    1. gameification
    2. health management
    3. social computing
    4. social machines

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    • Research-article

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    WWW '13
    Sponsor:
    • NICBR
    • CGIBR
    WWW '13: 22nd International World Wide Web Conference
    May 13 - 17, 2013
    Rio de Janeiro, Brazil

    Acceptance Rates

    WWW '13 Companion Paper Acceptance Rate 831 of 1,250 submissions, 66%;
    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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    Cited By

    View all
    • (2020)Artificial intelligence and machine learning in dynamic cyber risk analytics at the edgeSN Applied Sciences10.1007/s42452-020-03559-42:11Online publication date: 6-Oct-2020
    • (2019)Privacy, Trust and Ethical IssuesThe Theory and Practice of Social Machines10.1007/978-3-030-10889-2_4(149-200)Online publication date: 15-Feb-2019
    • (2019)Characterising Social MachinesThe Theory and Practice of Social Machines10.1007/978-3-030-10889-2_1(1-41)Online publication date: 15-Feb-2019
    • (2017)Does gamification increase engagement with online programs? A systematic reviewPLOS ONE10.1371/journal.pone.017340312:3(e0173403)Online publication date: 31-Mar-2017
    • (2016)Social Machines as an Approach to Group PrivacyGroup Privacy10.1007/978-3-319-46608-8_6(101-122)Online publication date: 29-Dec-2016
    • (2015)Is Gamification Effective in Motivating Exercise?Human-Computer Interaction: Interaction Technologies10.1007/978-3-319-20916-6_56(608-617)Online publication date: 21-Jul-2015
    • (2014)A Taxonomic Framework for Social MachinesSocial Collective Intelligence10.1007/978-3-319-08681-1_3(51-85)Online publication date: 23-Aug-2014
    • (undefined)A Storm in an IoT Cup: The Emergence of Cyber-Physical Social MachinesSSRN Electronic Journal10.2139/ssrn.3250383

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