Mind Your Tweet: Abusive Tweet Detection

• Published in: Speech and Computer Vol. 12997; pp. 704 - 715
• Main Authors: Tiwari, Paras, Rai, Sawan
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2021; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Abusive; CNN; Lexicon; LSTM
• ISBN: 9783030878016; 3030878015
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-030-87802-3_63

The abusive posts detection problem is more complicated than it seems due to its unseemly, unstructured noisy data and unpredictable context. The learning performance of the neural networks attracts researchers to get the highest performing output. Still, there are some limitations for noisy data while training for a neural network. In our work, we have proposed an approach that considers the assets of both the machine learning and neural network to get the most optimum result. Our approach performs with the F1 score of 92.79.