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Exploring Text Mining and Analytics for Applications in Public Security: An in-depth dive into a systematic literature review




Text Mining, Public Security, Systematic Literature Review, Technologies, Future Research Directions


Text mining and related analytics emerge as a technological approach to support human activities in extracting useful knowledge through texts in several formats. From a managerial point of view, it can help organizations in planning and decision-making processes, providing information that was not previously evident through textual materials produced internally or even externally. In this context, within the public/governmental scope, public security agencies are great beneficiaries of the tools associated with text mining, in several aspects, from applications in the criminal area to the collection of people's opinions and sentiments about the actions taken to promote their welfare. This article reports details of a systematic literature review focused on identifying the main areas of text mining application in public security, the most recurrent technological tools, and future research directions. The searches covered four major article bases (Scopus, Web of Science, IEEE Xplore, and ACM Digital Library), selecting 194 materials published between 2014 and the first half of 2021, among journals, conferences, and book chapters. There were several findings concerning the targets of the literature review, as presented in the results of this article.


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Author Biographies

Victor Diogho Heuer de Carvalho, Federal University of Alagoas

Assistant Professor in the Backland Campus at Universidade Federal de Alagoas (Delmiro Gouveia), working in the undergraduate courses of Management and Civil Engineering. He also is a Doctoral Candidate in the Graduate Program in Management Engineering at Universidade Federal de Pernambuco (Recife), and a member of the research group in Information and Decision Systems, currently working with research on applications of knowledge discovery tools in Public Security area.

Ana Paula Cabral Seixas Costa, Federal University of Pernambuco

Associate Professor in the Department of Production Engineering at Universidade Federal de Pernambuco (Recife), leader of the research group on Information and Decision Systems, member of the EURO Working Group on Behavioral Operational Research (EWG-BOR) and the EURO Working Group on Decision Support Systems (EWG-DSS). She has actively participated in international events in the area of Information Systems and Decision Support, such as AMCIS, GDN, and EWG-DSS International Conference, as well as in area streams in events such as IFORS and EURO. She has contributed with publication in important journals in her area of activity, such as IJIM, IJPM, IJTDM, and IJPE.


01/26/2022 — Updated on 01/19/2023


How to Cite

Carvalho, V. D. H. de, & Costa, A. P. C. S. (2023). Exploring Text Mining and Analytics for Applications in Public Security: An in-depth dive into a systematic literature review. In SciELO Preprints. (Original work published 2022)


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