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Cited by 67Information Systems Theories and ImplementationMobile Crowdsensing and CrowdsourcingInnovative Human-Technology Interaction

Understanding Human-Machine Networks: A Cross-Disciplinary Survey

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Tsvetkova, Milena, Yasseri, Taha, Meyer, Eric T., Pickering, J. Brian, Engen, Vegard, Walland, Paul, Lüders, Marika, Følstad, Asbjørn +1 more·2018·ACM Computing Surveys
DOI 10.1145/3039868
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Abstract

In the current hyperconnected era, modern Information and Communication Technology (ICT) systems form sophisticated networks where not only do people interact with other people, but also machines take an increasingly visible and participatory role. Such Human-Machine Networks (HMNs) are embedded in the daily lives of people, both for personal and professional use. They can have a significant impact by producing synergy and innovations. The challenge in designing successful HMNs is that they cannot be developed and implemented in the same manner as networks of machines nodes alone, or following a wholly human-centric view of the network. The problem requires an interdisciplinary approach. Here, we review current research of relevance to HMNs across many disciplines. Extending the previous theoretical concepts of socio-technical systems, actor-network theory, cyber-physical-social systems, and social machines, we concentrate on the interactions among humans and between humans and machines. We identify eight types of HMNs: public-resource computing, crowdsourcing, web search engines, crowdsensing, online markets, social media, multiplayer online games and virtual worlds, and mass collaboration. We systematically select literature on each of these types and review it with a focus on implications for designing HMNs. Moreover, we discuss risks associated with HMNs and identify emerging design and development trends.

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Authors
Tsvetkova, M., Yasseri, T., Meyer, E. T., Pickering, J. B., Engen, V., Walland, P., Lüders, M., Følstad, A., & Bravos, G.
Affiliations
  • University of Oxford (GB)
  • IT Innovation Center, University of Southampton, Southampton, UK
  • University of Southampton (GB)
  • SINTEF (NO)
  • Athens Technology Center (Greece) (GR)
ORCID
Venue
ACM Computing Surveys
Publisher
Association for Computing Machinery (ACM)
Published
2017-04-04
Volume
50
Issue
1
Pages
1-35
ISSN
  • 0360-0300 (ISSN-L)
  • 1557-7341
DOI
10.1145/3039868
OpenAlex
W2268451786
Cited by
67
References
19
Citations by year
2026: 5 · 2025: 3 · 2024: 7 · 2023: 12 · 2022: 7 · 2021: 7 · 2020: 4 · 2019: 8 · 2018: 5 · 2017: 6 · 2016: 2
FWCI
16.11
Type
journal article
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
  • ACM Computing Surveys (publishedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Bournemouth University Research Online (Bournemouth University) (submittedVersion)
  • London School of Economics and Political Science Research Online (London School of Economics and Political Science) (submittedVersion)
  • Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
  • arXiv (Cornell University)
Funders
European Union's Horizon 2020 research and innovation program (645043)
Topics
  • Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
  • Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
human-machine interaction, socio-technical systems, actor-network theory, cyber-physical-social systems, social machines, crowdsourcing, crowdsensing, search engines, digital markets, social media, online multiplayer games, virtual worlds, mass collaboration, network design

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