Version 1
: Received: 29 February 2024 / Approved: 1 March 2024 / Online: 1 March 2024 (18:30:13 CET)
How to cite:
De Carvalho, V.D.H.; Dos Santos, R.J.R.; Nepomuceno, T.C.C.; Poleto, T. Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions. Preprints2024, 2024030064. https://doi.org/10.20944/preprints202403.0064.v1
De Carvalho, V.D.H.; Dos Santos, R.J.R.; Nepomuceno, T.C.C.; Poleto, T. Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions. Preprints 2024, 2024030064. https://doi.org/10.20944/preprints202403.0064.v1
De Carvalho, V.D.H.; Dos Santos, R.J.R.; Nepomuceno, T.C.C.; Poleto, T. Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions. Preprints2024, 2024030064. https://doi.org/10.20944/preprints202403.0064.v1
APA Style
De Carvalho, V.D.H., Dos Santos, R.J.R., Nepomuceno, T.C.C., & Poleto, T. (2024). Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions. Preprints. https://doi.org/10.20944/preprints202403.0064.v1
Chicago/Turabian Style
De Carvalho, V.D.H., Thyago Celso Cavalcante Nepomuceno and Thiago Poleto. 2024 "Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions" Preprints. https://doi.org/10.20944/preprints202403.0064.v1
Abstract
Text mining is a technological trend often highlighted in the continuous exchange of information through interconnected media. Its applicability goes beyond private organizations, as the public sector also requires it to treat textual information regarding services offered. Within this scenario, public security emerges as a prominent user of text mining that seeks to ensure the construction of data and knowledgebases to support decision-making about law enforcement actions to ensure citizen welfare. The primary objectives of this article are: (i) to develop a survey to identify text mining applications, techniques, opportunities, and challenges in public security, and (ii) to outline research directions concerning these topics and provide insights so that interested researchers can develop new studies. The literature was searched within four databases: Scopus, IEEE Xplore, ACM Digital Library, and Web of Science. A filtering process was applied to extract the works most aligned with the target theme, resulting in the selection of 194 of the most relevant works for a literature review. There were identified nineteen key applications of text mining related to public security and the most recurrent techniques and technologies reported between 2014 to 2021, supporting outlining three axes for future directions: one with possible expansion of objectives for new research; another on changes and adaptations in scopes for the methodological context; and the last one on expansions and changes in application scenarios based on the literature.
Keywords
Text mining; Public security; Survey; Applications; Opportunities; Future Research Directions
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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