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Understanding the structure, characteristics, and future of collective intelligence using local and global bibliometric analyses
University Of Ottawa, Ottawa, Canada; North-West University, Potchefstroom, South Africa; National Research University Higher School Of Economics, Moscow, Russian Federation.ORCID iD: 0000-0002-2146-1506
Halmstad University, School of Business, Innovation and Sustainability.ORCID iD: 0000-0002-2427-3148
Scitech Strategies, Wayne, PA, United States.
Central European University, Vienna, Austria; Mohammed VI Polytechnic University, Ben Guerir, Morocco.
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2022 (English)In: Technological forecasting & social change, ISSN 0040-1625, E-ISSN 1873-5509, Vol. 178, article id 121561Article in journal (Refereed) Published
Abstract [en]

“Collective Intelligence” has been a popular area of research for more than a decade. We apply two different analytical approaches (local and global bibliometric analysis) to describe how this literature is organized and how it has evolved. A local approach focuses on the 3,138 articles indexed in the Scopus database where ‘collective intelligence’ is in the title, abstract, or keyword. A global approach reclassifies all of the Scopus documents into research communities using all (1.28 billion) citations in the database and proceeds to identify which research communities are populated by the 3,138 Collective Intelligence (CI) articles. These two approaches provide significantly different perspectives on how CI is structured, who the leaders of the field are, and how it is evolving. A synthesis of these two perspectives provides ideas for those who wish to contribute to the collective intelligence field. Our findings support the Kuhnian idea of research communities as a useful concept in bibliometric analysis. © 2022 The Authors.

Place, publisher, year, edition, pages
New York, NY: Elsevier, 2022. Vol. 178, article id 121561
Keywords [en]
Bibliometric analysis, Collective intelligence, Research communities
National Category
Media and Communications
Identifiers
URN: urn:nbn:se:hh:diva-46490DOI: 10.1016/j.techfore.2022.121561ISI: 000778411300005Scopus ID: 2-s2.0-85124695215OAI: oai:DiVA.org:hh-46490DiVA, id: diva2:1645960
Note

Funding: Russian Academic Excellence Project ‘5–100′

Available from: 2022-03-21 Created: 2022-03-21 Last updated: 2022-05-10Bibliographically approved

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Solberg Søilen, Klaus

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