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Social Machine: Comparison
Please note this is a comparison between Version 1 by Catherine Yang and Version 2 by Catherine Yang.

A social machine is a sociotechnical system in which human participants and computational technologies interact to produce outcomes that neither could achieve as effectively in isolation [1][2]. Social machine is particularly associated with Web-based environments, where digital platforms coordinate human contributions through computational processes, interfaces, and rules [1][3]. Participants may create and share content, contribute knowledge, classify information, solve problems, or coordinate collective activities, while technological components support communication, organize contributions, and process the resulting data. Examples include collaborative knowledge platforms, crowdsourcing systems, online communities, and citizen-science projects, in which individual contributions can be integrated into shared outputs. Social machines differ from conventional automated systems because human participation is an integral part of their operation rather than merely an external source of input [3][4]. Their effectiveness depends on the design of participation mechanisms, the distribution of tasks, the quality of communication, and the coordination between human judgment and computational processing. In knowledge management and communication, social machines enable distributed knowledge creation, collaborative problem-solving, and large-scale information exchange.

  • social machine
  • sociotechnical systems
  • social computing
  • knowledge sharing
  • collective intelligence
  • human–computer interaction

Knowledge Management and Sharing •  Communication • Social Sciences • Social Sciences

References

  1. Jim Hendler; Tim Berners-Lee; From the Semantic Web to social machines: A research challenge for AI on the World Wide Web. Artif. Intell. 2010, 174, 156-161. [CrossRef]
  2. Nigel Shadbolt; Kieron O’hara; David De Roure; Wendy Hall. The Theory and Practice of Social Machines; Springer Nature: Durham, NC, United States, 2019. [CrossRef]
  3. Paul Smart; Elena Simperl; Nigel Shadbolt. A Taxonomic Framework for Social Machines; Springer Nature: Durham, NC, United States, 2014; pp. 51-85. [CrossRef]
  4. Nello Cristianini; Teresa Scantamburlo; On social machines for algorithmic regulation. AI Soc. 2019, 35, 645-662. [CrossRef]
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