The evolution of citation graphs in artificial intelligence research

Morgan R. Frank, Dashun Wang, Manuel Cebrian, Iyad Rahwan*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

13 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)79-85
Number of pages7
JournalNature Machine Intelligence
Volume1
Issue number2
DOIs
StatePublished - Feb 1 2019

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Software

Fingerprint Dive into the research topics of 'The evolution of citation graphs in artificial intelligence research'. Together they form a unique fingerprint.

Cite this