Identification of offensive language in social media

Altin, Lutfiye Seda Mut

Identification of offensive language in social media

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Citation

Altin LSM. Identification of offensive language in social media. In: Lloret E, Saquete E, Martínez-Barco P, Sepílveda-Torres R, (eds.). Proceedings of the Doctoral Symposium of the XXXV International Conference of the Spanish Society for Natural Language Processing (SEPLN 2019); 2019 Sep 25; Bilbao, Espanya. Bilbao: SEPLN;2019. p. 50-5.

Abstract

Recent work shows that offensive language in social media is a serious problem that affects especially vulnerable groups. Therefore, systems designed to detect offensive language automatically have been the focus of attention of several works. Various Machine Learning approaches have been utilised for the classification of offensive text data. Within the scope of this research we aim to develop a neural network system that will effectively classify offensive text considering different aspects of it. In addition, multilingual and multi-task learning experiments are planned.
El uso de lenguaje ofensivo en las redes sociales es un problema que afecta especialmente a las personas vulnerables. Es por esta raz´on que el desarrollo de sistemas autom´aticos para la detecci´on de lenguaje ofensivo es una tarea de considerable importancia social. En esta investigaci´on nos proponemos desarrollar sistemas basados en t´ecnicas recientes de aprendizaje de maquina tales como las redes neuronales para la clasificaci´on de lenguaje ofensivo. As´ı mismo nos proponemos realizar experimentos con datos multiling¨ues (espa˜nol e ingl´es) y la aplicaci´on de t´ecnicas multitarea que est´en relacionadas con este problema.

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Comunicació presentada a: XXXV International Conference of the Spanish Society for Natural Language Processing (SEPLN 2019), celebrat el 25 de setembre de 2019, a Bilbao, Espanya