Probabilistic Impact Score Generation using Ktrain-BERT to Identify Hate Words from Twitter Discussions

Understand

Social media has seen a worrying rise in hate speech in recent times.

• Branching to several distinct categories of cyberbullying, gender discrimination, or racism, the combined label for such derogatory content can be classified as toxic content in general.
• This paper presents experimentation with a Keras wrapped lightweight BERT model to successfully identify hate speech and predict probabilistic impact score for the same to extract the hateful words within sentences.
• The dataset used for this task is the Hate Speech and Offensive Content Detection (HASOC 2021) data from FIRE 2021 in English.