OFFENSIVE LANGUAGE DETECTION THROUGH TEXT CLASSIFICATION

In this book, we propose a modular text classification pipeline on social media datasets focusing on Twitter. Our proposed approach is to leverage a modular development that allows easy use for combining different text classification components. This work's main contribution is that it presents a new modular text classification pipeline to facilitate benchmarking by conducting a detailed analytical study of the best-performing approaches, features, and embeddings reported by the state-of-the-art.

Autorentext
Dr. Naseem Khayum has published 9 SCI peer-reviewed, 06 International conference publications and expertise in the field of optimization of different processes. P. Fiza Banu, graduated from JNTUA College of Engineering in 2024. She is an expert in the field of Machine Learning and its Applications.