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：在线社交网络已成为我们日常生活的基本组成部分。不幸的是，这些平台也成为仇恨言论的舞台。主流社交网络制定了反对仇恨言论的规范化规则。因此，诸如Parler和Gab等倡导并声称提供自由言论平台的社交网络应运而生。这些平台已成为针对不同目标的仇恨言论聚集地。本文提出了一种用于检测仇恨言论及其目标的流水线方法，并将其用于构建Parler仇恨目标分布。该流水线包含两个模型：一个用于仇恨言论检测，另一个用于目标分类，两者均基于BERT架构，并采用反向翻译和数据预处理技术以提升性能。本工作所使用的源代码及其他相关资源详见：https://github.com/NadavSc/HateRecognition.git