A descriptive analysis of collective intelligence publications since 2000, and the emerging influence of artificial intelligence. Issue 1 (22nd August 2022)

• Record Type: Journal Article
• Authors: Berditchevskaia, Aleks; Maliaraki, Eirini; Stathoulopoulos, Konstantinos
• Is Part Of: Collective intelligence. Volume 1:Issue 1(2022)
• Publication Date: 2022-08-22
• Subjects: Collective intelligence -- artificial intelligence -- bibliometrics -- crowdsourcing -- descriptive analysis; Computational intelligence -- Periodicals; Collective behavior -- Periodicals; Swarm intelligence -- Periodicals; 006.3
• DOI: 10.1177/26339137221107924
• Languages: English
• ISSNs: 2633-9137

Abstract

Collective intelligence (CI) is an interdisciplinary field that draws on a wide range of academic disciplines but has struggled to capitalise on cross-pollination between fields, particularly ones which do not self-identify with the collective intelligence label. Past studies have largely undertaken a qualitative and manual approach to classifying different trends in the CI literature. This method risks missing a significant proportion of publications in the field. To this end, we present the first attempt to reflect the field to itself through an automated and quantitative descriptive approach using Microsoft Academic Graph (MAG) to collect and analyse 39, 334 CI papers. We further focus our investigation on a subset of the CI literature, at the intersection of artificial intelligence (AI) and CI to understand how these two fields are interacting. We show that while the annual number of CI-only publications has remained steady since 2015, AI+CI research has continued to increase. Publications in the crossover of AI+CI are growing at a faster rate than CI-only papers but show less topical and disciplinary breadth. This may be having a spillover effect on the topical focus of non-AI collective intelligence research. We hope this analysis sheds more light on the dynamics of the CI ecosystem.