Detection of violent speech against women in Mexican tweets using an active learning approach

IF 1.3 4区 工程技术 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Grisel Miranda-Piña;Roberto Alejo;Eréndira Rendón-Lara;Vicente García
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引用次数: 0

Abstract

In Latin American and Caribbean States the verbal violence against women on social networks, such as Twitter, is a serious threat that has been addressed through the implementation of social norms, public policies, and social movements. Nevertheless, a challenge is the effective and automatic real-time detection of violent tweets. In this sense, traditional machine learning algorithms have been proposed to tackle social issues where the training process is performed in a static manner. However, considering that Twitter is a dynamic environment where a vast of tweets are generated each second, it requires powerful machine learning algorithms that could exploit this pool of unlabeled data to be incorporated into the model through continuous updates. This paper explores an active learning method based on uncertainty sampling, which identifies the most confusing tweets to be labeled by an expert in real-time. This focused selection prioritizes which data can be used to train a multilayer perceptron that can achieve a better performance with fewer training samples. Experimental results show that including new samples yields promising results, increasing the AUC from 0.8712 to 0.8833.
利用主动学习方法检测墨西哥推文中针对妇女的暴力言论
在拉丁美洲和加勒比国家,社交网络(如 Twitter)上针对妇女的语言暴力是一个严重威胁,已通过实施社会规范、公共政策和社会运动加以解决。然而,有效、自动地实时检测暴力推文是一项挑战。在这个意义上,传统的机器学习算法已被提出来解决社会问题,其训练过程是以静态方式进行的。然而,考虑到 Twitter 是一个动态环境,每秒钟都会产生大量的推文,因此需要强大的机器学习算法来利用这些未标记的数据池,通过不断更新将其纳入模型。本文探讨了一种基于不确定性采样的主动学习方法,该方法可识别出最容易混淆的推文,并由专家进行实时标注。这种有针对性的选择会优先考虑哪些数据可用于训练多层感知器,从而以更少的训练样本获得更好的性能。实验结果表明,加入新样本会产生很好的效果,AUC 从 0.8712 提高到 0.8833。
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来源期刊
IEEE Latin America Transactions
IEEE Latin America Transactions COMPUTER SCIENCE, INFORMATION SYSTEMS-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
3.50
自引率
7.70%
发文量
192
审稿时长
3-8 weeks
期刊介绍: IEEE Latin America Transactions (IEEE LATAM) is an interdisciplinary journal focused on the dissemination of original and quality research papers / review articles in Spanish and Portuguese of emerging topics in three main areas: Computing, Electric Energy and Electronics. Some of the sub-areas of the journal are, but not limited to: Automatic control, communications, instrumentation, artificial intelligence, power and industrial electronics, fault diagnosis and detection, transportation electrification, internet of things, electrical machines, circuits and systems, biomedicine and biomedical / haptic applications, secure communications, robotics, sensors and actuators, computer networks, smart grids, among others.
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