Characterising Research Areas in the field of AI

TL;DR

This paper performs a bibliometric analysis of 257,000 AI articles to identify main research themes, track their evolution over time, and provide insights into the field's growth and focus areas.

Contribution

It introduces a comprehensive clustering-based approach to characterize AI research areas and their development using large-scale bibliometric data.

Findings

Deep learning, machine learning, and IoT are prominent themes.

Research interest in AI has significantly increased over time.

Themes have evolved with emerging topics gaining prominence.

Abstract

Interest in Artificial Intelligence (AI) continues to grow rapidly, hence it is crucial to support researchers and organisations in understanding where AI research is heading. In this study, we conducted a bibliometric analysis on 257K articles in AI, retrieved from OpenAlex. We identified the main conceptual themes by performing clustering analysis on the co-occurrence network of topics. Finally, we observed how such themes evolved over time. The results highlight the growing academic interest in research themes like deep learning, machine learning, and internet of things.