Oppositeness-based Hate Speech Detection

Identification of hate speech (HS) on social media became significant with the vast amount of web data availability in social media platforms. Even though there exist many HS detection machine learning algorithms nurtured from modern concepts such as deep learning and artificial intelligence, HS detection is still a challenge as humans find loopholes to trick those algorithms. Therefore, the need of implementing new HS detection models, retraining, and detecting the model drift of existing has become a non-ending provocation. Hence, the study is based on a novel approach in HS detection using oppositeness measure.