Towards NLP with Deep Learning: Convolutional Neural Networks and Recurrent Neural Networks for Offensive Language Identification in Social Media

Abstract

This short paper presents the design decisions taken and challenges encountered in completing SemEval Task 6, which poses the problem of identifying and categorizing offensive language in tweets. Our proposed solutions explore Deep Learning techniques, Linear Support Vector classification and Random Forests to identify offensive tweets, to classify offenses as targeted or untargeted and eventually to identify the target subject type.

References in corpus (2)

• Distributed Representations of Words and Phrases and their Compositionality
• Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Cited by in corpus (1)

• SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)