Exploring the application of machine learning to expert evaluation of research impact.

ABSTRACT: The objective of this study is to investigate the application of machine learning techniques to the large-scale human expert evaluation of the impact of academic research. Using publicly available impact case study data from the UK's Research Excellence Framework (2014), we trained five machine learning models on a range of qualitative and quantitative features, including institution, discipline, narrative style (explicit and implicit), and bibliometric and policy indicators. Our work makes two key contributions. Based on the accuracy metric in predicting high- and low-scoring impact case studies, it shows that machine learning models are able to process information to make decisions that resemble those of expert evaluators. It also provides insights into the characteristics of impact case

SUBMITTER: Williams K 

PROVIDER: S-EPMC10399885 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature