An Exploration of State-of-the-art Methods for Offensive Language Detection
arXiv:1903.07445v21 citations
AI Analysis
This work addresses the problem of detecting offensive language for content moderation, but it is incremental as it explores existing methods without introducing new paradigms.
The paper investigates various architectures and feature vector generation methods for offensive language detection, demonstrating their effectiveness on small, noisy datasets like OLID.
We provide a comprehensive investigation of different custom and off-the-shelf architectures as well as different approaches to generating feature vectors for offensive language detection. We also show that these approaches work well on small and noisy datasets such as on the Offensive Language Identification Dataset (OLID), so it should be possible to use them for other applications.