Mapping the (anti-)corruption field: key topics and changing trends, 1968–2020

Joseph Pozsgai-Alvarez () and Iván Pastor Sanz ()
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Joseph Pozsgai-Alvarez: Kyoto University
Iván Pastor Sanz: University of Valladolid

Journal of Computational Social Science, 2021, vol. 4, issue 2, No 18, 881 pages

Abstract: Abstract As research on (anti-)corruption continues to accelerate, the heterogeneity of perspectives that have emerged in the field complicates the identification of key topics and trends, limiting our capacity to set meaningful research priorities, risking the waste of time and funds, and potentially broadening the gap between scholarly production and policy necessities. To help elucidate this morass, we use the Latent Dirichlet Allocation (LDA) algorithm to classify a dataset of 5417 publications listed in the Global Anticorruption Blog’s (GAB) Anticorruption Bibliography. The results allow us to recognize eight main topics in the literature, as well as their evolution over the past 2 decades in terms of relative attention (as measured by citation count) and publication rates. The topics and trends found here invite us to reflect on the current structure of the (anti-)corruption field, and to draw attention to persistent—and emerging—gaps.

Keywords: Corruption; Corpus; Machine learning; Bibliometrics; Interdisciplinary (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s42001-021-00110-2

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