Hateminers : Detecting Hate speech against Women

2018-12-17 · Punyajoy Saha, Binny Mathew, Pawan Goyal, Animesh Mukherjee

With the online proliferation of hate speech, there is an urgent need for systems that can detect such harmful content. In this paper, We present the machine learning models developed for the Automatic Misogyny Identification (AMI) shared task at EVALITA 2018. We generate three types of features: Sentence Embeddings, TF-IDF Vectors, and BOW Vectors to represent each tweet. These features are then concatenated and fed into the machine learning models. Our model came First for the English Subtask A and Fifth for the English Subtask B. We release our winning model for public use and it's available at https://github.com/punyajoy/Hateminers-EVALITA.

📄 PDF Abstract BibTeX arXiv:1812.06700

Code (2)

punyajoy/Hateminers-EVALITA 공식 구현

hate-alert/HateALERT-EVALITA

Tasks

BIG-bench Machine Learning Hate Speech DetectionSentenceSentence Embeddings

SINAI at SemEval-2019 Task 5: Ensemble learning to detect hate speech against inmigrants and women in English and Spanish tweets

2019-06-01 · SEMEVAL 2019 6 · Flor Miriam Plaza-del-Arco, M. Dolores Molina-Gonz{\'a}lez, Maite Martin, L. Alfonso Ure{\~n}a-L{\'o}pez

Misogyny and xenophobia are some of the most important social problems. With the in- crease in the use of social media, this feeling ofhatred towards women and immigrants can be more easily expressed, therefore it can ca…

Ensemble Learning

SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter

2019-06-01 · SEMEVAL 2019 6 · Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza 외

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…

MineriaUNAM at SemEval-2019 Task 5: Detecting Hate Speech in Twitter using Multiple Features in a Combinatorial Framework

2019-06-01 · SEMEVAL 2019 6 · Luis Enrique Argota Vega, Jorge Carlos Reyes-Maga{\~n}a, Helena G{\'o}mez-Adorno, Gemma Bel-Enguix

This paper presents our approach to the Task 5 of Semeval-2019, which aims at detecting hate speech against immigrants and women in Twitter. The task consists of two sub-tasks, in Spanish and English: (A) detection of ha…

General Classification POS

LT3 at SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval)

2019-06-01 · SEMEVAL 2019 6 · Nina Bauwelinck, Gilles Jacobs, V{\'e}ronique Hoste, Els Lefever

This paper describes our contribution to the SemEval-2019 Task 5 on the detection of hate speech against immigrants and women in Twitter (hatEval). We considered a supervised classification-based approach to detect hate …

Classification General Classification

INF-HatEval at SemEval-2019 Task 5: Convolutional Neural Networks for Hate Speech Detection Against Women and Immigrants on Twitter

2019-06-01 · SEMEVAL 2019 6 · Alison Ribeiro, N{\'a}dia Silva

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 Detection Word Embeddings