Artículo

Specialization trends in economics research: A large‐scale study using natural language processing and citation analysis

Resumen

This article conducts a comprehensive analysis of specialization trends within and across fields of economics research. We collect data on 24,273 articles published between 1970 and 2016 in general research economics outlets and employ machine learning techniques to enrich the collected data. Results indicate that theory and econometric methods papers are becoming increasingly specialized, with a narrowing scope and steady or declining citations from outside economics and from other fields of economics research. Conversely, applied papers are covering a broader range of topics, receiving more extramural citations from fields like medicine, and psychology. Trends in applied theory articles are unclear.
https://doi.org/10.1111/ecin.13261
Specialization trends in economics research: A large‐scale study using natural language processing and citation analysis
2024
bronze
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ecin.13261
Sebastian Galiani; Ramiro H. Gálvez; Ian Nachman
University of Maryland College Park Maryland USA; National Bureau of Economic Research (NBER) Cambridge Massachusetts USA; Universidad Torcuato Di Tella Ciudad de Buenos Aires Argentina; Brown University Providence Rhode Island USA
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