Machine Learning Applied to Gender Violence: A Systematic Mapping Study

Cristian-Camilo Pinto-Muñoz, Jhon-Alex Zuñiga-Samboni, Hugo-Armando Ordoñez-Erazo
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Abstract

Machine Learning (ML) has positioned itself as one of the best tools to address different problems thanks to its data processing capabilities, as well as the different models, algorithms, and predictive factors that help to solve defined problems. Therefore, this article presents a systematic mapping from 2018 to 2023 focused on the application of ML to gender-based violence. The methodology followed for this study is based on the definition of elements such as research questions, search strings, bibliographic sources, and inclusion and exclusion criteria. The research results allow us to understand the benefits and challenges of using artificial intelligence, precisely one of its branches, ML, to help combat problems in different areas of society, such as education, health, and violence, among others. It also identifies the countries where ML is being researched and the contexts it is applied to. The study discusses the application of ML to combat gender-based violence. After conducting a literature review, beneficial results were found in the application of artificial intelligence and ML. The results obtained in the different articles showed a predictive capacity and improvements compared to currently used systems. However, despite the positive results, no evidence of the development of an ML model or algorithm applied to gender-based violence in Colombia was found in the review.
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将机器学习应用于性别暴力:系统绘图研究
机器学习(ML)凭借其数据处理能力,以及有助于解决既定问题的不同模型、算法和预测因素,已被定位为解决不同问题的最佳工具之一。因此,本文介绍了从 2018 年到 2023 年的系统规划,重点是将 ML 应用于性别暴力。本研究采用的方法基于对研究问题、搜索字符串、书目来源、纳入和排除标准等要素的定义。研究结果让我们了解了使用人工智能(正是其分支之一--ML)帮助解决教育、卫生和暴力等不同社会领域问题的益处和挑战。它还确定了正在研究 ML 的国家及其应用环境。本研究讨论了应用 ML 打击性别暴力的问题。在进行文献综述后,发现了人工智能和 ML 应用方面的有益成果。不同文章中获得的结果表明,与目前使用的系统相比,人工智能具有预测能力并有所改进。然而,尽管取得了积极成果,但在审查中并未发现开发出适用于哥伦比亚性别暴力的人工智能模型或算法的证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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