Hate and Aggression Detection in Social Media Over Hindi English Language

Author:

Pareek Kapil1,Choudhary Arjun1,Tripathi Ashish2,Mishra K. K.3,Mittal Namita4

Affiliation:

1. Sardar Patel University of Police, Security, and Criminal Justice, Jodhpur, India

2. G. L. Bajaj Institute of Technology and Management, Greater Noida, India

3. Motilal Nehru National Institute of Technology, Allahabad, India

4. Malaviya National Institute of Technology, Jaipur, India

Abstract

In today’s time, everyone is familiar with social media platforms. It is quite helpful in connecting people. It has many advantages and some disadvantages too. Currently, in social media, hate and aggression have become a huge problem. On these platforms, many people make inflammatory posts targeting any person or society by using code mixed language, due to which many problems arise in the society. At the current time, much research work is being done on English language-related social media posts. The authors have focused on code mixed language. Authors have also tried to focus on sentences that do not use abusive words but contain hatred-related remarks. In this research, authors have used Natural Language Processing (NLP). Authors have applied Fasttext word embedding to the dataset. Fasttext is a technique of NLP. Deep learning (DL) classification algorithms were applied thereafter. In this research, two classifications have been used i.e. Convolutional Neural Network (CNN) and Bidirectional LSTM (Bi-LSTM).

Publisher

IGI Global

Subject

Pharmacology (medical)

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