Ara-Women-Hate: An Annotated Corpus Dedicated to Hate Speech Detection against Women in the Arabic Community
In this paper, an approach for hate speech detection against women in the Arabic community on social media (e.g. Youtube) is proposed. In the literature, similar works have been presented for other languages such as English. However, to the best of our knowledge, not much work has been conducted in the Arabic language. A new hate speech corpus (Arabic_fr_en) is developed using three different annotators. For corpus validation, three different machine learning algorithms are used, including deep Convolutional Neural Network (CNN), long short-term memory (LSTM) network and Bi-directional LSTM (Bi-LSTM) network. Simulation results demonstrate the best performa
Code (0)
등록된 구현이 없습니다.
Tasks
Hate Speech DetectionSimilar Papers 제목 키워드 기반
HateBR: A Large Expert Annotated Corpus of Brazilian Instagram Comments for Offensive Language and Hate Speech Detection
Due to the severity of the social media offensive and hateful comments in Brazil, and the lack of research in Portuguese, this paper provides the first large-scale expert annotated corpus of Brazilian Instagram comments …
BIG-bench Machine LearningBinary ClassificationHate Speech DetectionSemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in Spanish and English messages extracted from Twitter. The task is organized in two related…
Examining a hate speech corpus for hate speech detection and popularity prediction
As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter co…
Hate Speech DetectionUTFPR at SemEval-2019 Task 5: Hate Speech Identification with Recurrent Neural Networks
In this paper we revisit the problem of automatically identifying hate speech in posts from social media. We approach the task using a system based on minimalistic compositional Recurrent Neural Networks (RNN). We tested…
INF-HatEval at SemEval-2019 Task 5: Convolutional Neural Networks for Hate Speech Detection Against Women and Immigrants on Twitter
In this paper, we describe our approach to detect hate speech against women and immigrants on Twitter in a multilingual context, English and Spanish. This challenge was proposed by the SemEval-2019 Task 5, where particip…
Hate Speech DetectionWord Embeddings