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The evolution of citation graphs in artificial intelligence research


As artificial intelligence (AI) applications see wider deployment, it becomes increasingly important to study the social and societal implications of AI adoption. Therefore, we ask: are AI research and the fields that study social and societal trends keeping pace with each other? Here, we use the Microsoft Academic Graph to study the bibliometric evolution of AI research and its related fields from 1950 to today. Although early AI researchers exhibited strong referencing behaviour towards philosophy, geography and art, modern AI research references mathematics and computer science most strongly. Conversely, other fields, including the social sciences, do not reference AI research in proportion to its growing paper production. Our evidence suggests that the growing preference of AI researchers to publish in topic-specific conferences over academic journals and the increasing presence of industry research pose a challenge to external researchers, as such research is particularly absent from references made by social scientists.

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Fig. 1: Citation patterns among CS subfields identify areas of AI-related research.
Fig. 2: The referencing strength between AI and other sciences is declining.
Fig. 3: AI research is increasingly dominated by only a few research institutions and AI-specific conferences.
Fig. 4: Industry is increasingly central to AI research, but industry-authored AI papers are referenced less often by other academic fields.


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The authors would like to thank E. Moro and Z. Epstein for their comments.

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M.R.F. and D.W. processed data and produced figures. All authors wrote the manuscript.

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Correspondence to Iyad Rahwan.

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Frank, M.R., Wang, D., Cebrian, M. et al. The evolution of citation graphs in artificial intelligence research. Nat Mach Intell 1, 79–85 (2019).

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