Cyberbullying Detection Through Acoustic and Linguistic Analysis
Rafik Aimen Silakhal, Sara Zekri, Osman Salem, Ahmed Mehaoua · 2023
In this article, we present a method for detecting cyberbullying that goes beyond understanding the text's content and also considers the underlying intent. Our approach involves analyzing both the acoustic and linguistic features of audio to gain insights into the emotional intent conveyed in the text. Using the librosa library, we extract acoustic features from audio files to identify whether the emotions expressed are aggressive or non-aggressive. We then combine this information with the results of linguistic analysis to develop a comprehensive understanding of the text's content. By incorporating the emotional aspect, our method enables more precise and nuanced identification of cyberbullying instances.