Machine learning meets the Journal of Public Budgeting and Finance: Topics and trends over 40 years-Reference-Cited by-同舟云学术

Machine learning meets the Journal of Public Budgeting and Finance: Topics and trends over 40 years

Published:2023-09-04 Issue:4 Volume:43 Page:3-23
ISSN:0275-1100
Container-title:Public Budgeting & Finance
language:en
Short-container-title:Public Budgeting & Finance

Author:

Chen Can¹,Xiao Shiyang²,Zhao Boyuan³

Affiliation:

1. Andrew Young School of Policy Studies Georgia State University Atlanta Georgia USA

2. Maxwell School of Citizenship and Public Affairs Syracuse University, Syracuse New York New York USA

3. Department of Public Policy and Administration Florida International University Miami Florida USA

Abstract

AbstractThis research aims to mark the 40th anniversary of Public Budgeting & Finance (PB&F) by providing a retrospective of its journey over the past 40 years using the method of an unsupervised machine learning technique—structural topic modeling (STM). The study identifies 15 key thematic topics that most optimally represent the 1028 articles that were published in the studied period from 1981 to 2020. Furthermore, the study reveals the dynamic changes in the popularity of each thematic topic over time. This research identifies past and emerging research trends in PB&F to help scholars and students keep sight of the overall landscape of public budgeting and finance literature.

Publisher

Wiley

Subject

Public Administration,Economics and Econometrics,Finance

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/pbaf.12348

Reference30 articles.

1. An Introduction to Text Mining

2. Smart literature review: a practical topic modelling approach to exploratory literature review

3. Public Financing in Developing and Transition Countries

4. Research topics and trends in the maritime transport: A structural topic model

5. From Symbols to Embeddings: A Tale of Two Representations in Computational Social Science