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

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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.

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Availability of data and materials

Upon request.

Code availability

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Notes

  1. https://globalanticorruptionblog.com/.

  2. GAB’s collections has also been made available as a web-hosted searchable database in the form of the The ACE Digital Library, built by Gawthorpe and Pozsgai-Alvarez’s [45] and hosted by non-governmental organization Global Integrity.

  3. https://www.cochranelibrary.com/cdsr/reviews.

  4. While it is not possible to quantify the rate of recall—that is, the percentage of the universe of (anti-)corruption publications that is included in the corpus—and, therefore, various sources of bias are possible (GAB does not publish the methodology used to update its bibliographic collection), GAB’s recognition and praise among corruption scholars ultimately leaves it as the most prominent (even if potentially flawed) source of data until an improved collection emerges.

  5. The methods used for training LDA models evolve over time, becoming more efficient and easy to implement. This is the case of Gibbs sampling, which combines simplicity with high accuracy [48].

  6. Stopwords are defined as words in a language that are so common that their information value is practically null.

  7. The process of automatically truncating words to the root can be achieved using different methods. In our case, we use Python to perform the root transformation and train the model. Specifically, we use the ‘spaCy’ library, which contains many different functions for natural language processing. For a small number of words, however, spaCy may fail to produce the correct lemma—an issue that is not exclusive to this library. Despite the recognized limitation, we decided to use spaCy due to the higher reliability offered in comparison to other alternatives, particularly the manual identification of thousand words (which is itself also prone to producing mistakes). Moreover, as each topic is defined as a word distribution with different weights, it can be considered a small limitation with no relevant impact on the results.

  8. The publications mentioned here and in subsequent topics were selected from among the top twenty publications ranked by number of citations.

  9. Trend lines have been estimated following a quadratic function. This approach allows us to obtain a better representation of the evolution of publications and weights against other alternatives such as a linear function, aiming to describe only the major trends without missing significant but temporary changes across the period evaluated.

  10. Excerpt from his Annual Meetings Address, available at http://documents.worldbank.org/curated/en/135801467993234363/text/People-and-development-annual-meetings-address-by-James-D-Wolfensohn-President.txt.

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  1. Center for Southeast Asian Studies, Kyoto University, 46 Shimoadachi-cho, Yoshida, Sakyo-ku, Kyoto, 606-8501, Japan

    Joseph Pozsgai-Alvarez

  2. School of Business and Economics, University of Valladolid, Avda. Valle del Esgueva 6, 47011, Valladolid, Spain

    Iván Pastor Sanz

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Pozsgai-Alvarez, J., Pastor Sanz, I. Mapping the (anti-)corruption field: key topics and changing trends, 1968–2020. J Comput Soc Sc 4, 851–881 (2021). https://doi.org/10.1007/s42001-021-00110-2

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