Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis

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. Res...

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Detalles Bibliográficos
Autores principales: Galiani, Sebastián, Gálvez, Ramiro, Nachman, Ian
Formato: Artículo acceptedVersion
Lenguaje:Inglés
Publicado: Economic Inquiry (e-ISSN 1465-7295) 2024
Materias:
Fields of economics research
Natural Language Processing
Econometría
Econometrics
Data Analysis
Machine Learning
Aprendizaje automático
Citation analysis
Acceso en línea:https://repositorio.utdt.edu/handle/20.500.13098/13136
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4460244
Aporte de:
Repositorio Digital Universidad Torcuato Di Tella de Universidad Torcuato Di Tella
id I57-R163-20.500.13098-13136
record_format dspace
spelling I57-R163-20.500.13098-131362024-11-08T07:00:20Z Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis Galiani, Sebastián Gálvez, Ramiro Nachman, Ian Fields of economics research Natural Language Processing Econometría Econometrics Data Analysis Machine Learning Aprendizaje automático Citation analysis 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. (JEL A11, A14) Por motivos relacionados con los derechos de autor este documento solo puede ser consultado en la Biblioteca Di Tella. Para reservar una cita podés ponerte en contacto con repositorio@utdt.edu./// De acuerdo a las condiciones editoriales acordada entre los autores y la revista Economic Inquiry (e-ISSN 1465-7295) este artículo podrá descargarse libremente de este Repositorio a partir del 02/11/2025/// Citar: Galiani, S., Gálvez, R. H., & Nachman, I. (2024). Specialization trends in economics research: A large‐scale study using natural language processing and citation analysis. Economic Inquiry. Portico. https://doi.org/10.1111/ecin.13261 2024-11-07T21:18:34Z 2024-11-07T21:18:34Z 2024-11-02 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion https://repositorio.utdt.edu/handle/20.500.13098/13136 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4460244 eng Economic Inquiry (e-ISSN 1465-7295) info:eu-repo/semantics/restrictedAccess http://rightsstatements.org/page/InC/1.0/?language=es 38 p. application/pdf application/pdf Economic Inquiry (e-ISSN 1465-7295)
institution Universidad Torcuato Di Tella
institution_str I-57
repository_str R-163
collection Repositorio Digital Universidad Torcuato Di Tella
language Inglés
orig_language_str_mv eng
topic Fields of economics research
Natural Language Processing
Econometría
Econometrics
Data Analysis
Machine Learning
Aprendizaje automático
Citation analysis
spellingShingle Fields of economics research
Natural Language Processing
Econometría
Econometrics
Data Analysis
Machine Learning
Aprendizaje automático
Citation analysis
Galiani, Sebastián
Gálvez, Ramiro
Nachman, Ian
Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis
topic_facet Fields of economics research
Natural Language Processing
Econometría
Econometrics
Data Analysis
Machine Learning
Aprendizaje automático
Citation analysis
description 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. (JEL A11, A14)
format Artículo
acceptedVersion
author Galiani, Sebastián
Gálvez, Ramiro
Nachman, Ian
author_facet Galiani, Sebastián
Gálvez, Ramiro
Nachman, Ian
author_sort Galiani, Sebastián
title Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis
title_short Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis
title_full Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis
title_fullStr Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis
title_full_unstemmed Specialization Trends in Economics Research: A Large-Scale Study Using Natural Language Processing and Citation Analysis
title_sort specialization trends in economics research: a large-scale study using natural language processing and citation analysis
publisher Economic Inquiry (e-ISSN 1465-7295)
publishDate 2024
url https://repositorio.utdt.edu/handle/20.500.13098/13136
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4460244
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