The Artificial Intelligence research field sits at the intersection of several overlapping spheres (academia, industry, media), each with their own logics and commitments. The influence of research within these worlds is studied through a number of bibliometric methods, including citation metrics for measuring influence within academia, and counts of patents and news-media mentions for influence in industry and the media. Using a large-scale, publicly-available dataset of research outputs, we compare the topical content of outputs that are highly influential in each of these worlds. We identify significant differences between the content of influential research in these worlds, indicating that the academic, industry and media worlds value different aspects of the Artificial Intelligence field. These differences provide new insights on the evaluation of research produced within the Artificial Intelligence field.
Berman, G., Williams, K. & Michalska, S. (2023). Investigating the influence of AI research topics in the academic, public, and industry spheres [version 1; peer review: 1 minor revision, 1 accepted, 1 major revision] [preprint]. 27th International Conference on Science, Technology and Innovation Indicators (STI 2023). https://doi.org/10.55835/6442070e78340aab60459654