JOURNAL ARTICLE

Hate and Aggression Detection in Social Media Over Hindi English Language

Kapil PareekArjun ChoudharyAshish TripathiK. K. MishraNamita Mittal

Year: 2022 Journal:   International Journal of Software Science and Computational Intelligence Vol: 14 (1)Pages: 1-20   Publisher: IGI Global

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).

Keywords:
Computer science Hatred Word embedding Social media Artificial intelligence Focus (optics) Convolutional neural network Natural language processing Code (set theory) Language identification Word (group theory) Embedding Natural language World Wide Web Linguistics Political science

Metrics

16
Cited By
2.94
FWCI (Field Weighted Citation Impact)
28
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Hate Speech and Cyberbullying Detection
Physical Sciences →  Computer Science →  Artificial Intelligence
Spam and Phishing Detection
Physical Sciences →  Computer Science →  Information Systems
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