Online social networks have become a fundamental component of our everyday life. Unfortunately, these platforms are also a stage for hate speech. Popular social networks have regularized rules against hate speech. Consequently, social networks like Parler and Gab advocating and claiming to be free speech platforms have evolved. These platforms have become a district for hate speech against diverse targets. We present in our paper a pipeline for detecting hate speech and its targets and use it for creating Parler hate targets' distribution. The pipeline consists of two models; one for hate speech detection and the second for target classification, both based on BERT with Back-Translation and data pre-processing for improved results. The source code used in this work, as well as other relevant sources, are available at: https://github.com/NadavSc/HateRecognition.git
翻译:网络社交平台已成为我们日常生活的重要组成部分。不幸的是,这些平台也是仇恨言论的场所。流行的社交网络有规定的反对仇恨言论的规则。因此,标榜为自由发言平台的社交网络如Parler和Gab正在不断发展。这些平台已经成为针对不同目标的仇恨言论的场所。本文提出了一种检测仇恨言论及其目标的流水线工作流,并将其用于创建Parler平台的仇恨目标分布。流水线由两个模型组成:一个用于检测仇恨言论,另一个用于目标分类,均基于具有后向翻译和数据预处理的BERT以获得更好的结果。本文使用的源代码以及其他相关资源可从此处获取:https://github.com/NadavSc/HateRecognition.git