Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model

11/02/2021
by   Hind Saleh, et al.
0

The enormous amount of data being generated on the web and social media has increased the demand for detecting online hate speech. Detecting hate speech will reduce their negative impact and influence on others. A lot of effort in the Natural Language Processing (NLP) domain aimed to detect hate speech in general or detect specific hate speech such as religion, race, gender, or sexual orientation. Hate communities tend to use abbreviations, intentional spelling mistakes, and coded words in their communication to evade detection, adding more challenges to hate speech detection tasks. Thus, word representation will play an increasingly pivotal role in detecting hate speech. This paper investigates the feasibility of leveraging domain-specific word embedding in Bidirectional LSTM based deep model to automatically detect/classify hate speech. Furthermore, we investigate the use of the transfer learning language model (BERT) on hate speech problem as a binary classification task. The experiments showed that domainspecific word embedding with the Bidirectional LSTM based deep model achieved a 93 achieved up to 96 speech datasets.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 9

10/01/2020

Detecting White Supremacist Hate Speech using Domain Specific Word Embedding with Deep Learning and BERT

White supremacists embrace a radical ideology that considers white peopl...
11/19/2019

Towards non-toxic landscapes: Automatic toxic comment detection using DNN

The spectacular expansion of the Internet led to the development of a ne...
03/16/2021

dictNN: A Dictionary-Enhanced CNN Approach for Classifying Hate Speech on Twitter

Hate speech on social media is a growing concern, and automated methods ...
06/01/2020

Sarcasm Detection using Context Separators in Online Discourse

Sarcasm is an intricate form of speech, where meaning is conveyed implic...
01/23/2018

The Enemy Among Us: Detecting Hate Speech with Threats Based 'Othering' Language Embeddings

Offensive or antagonistic language targeted at individuals and social gr...
11/28/2017

Surfacing contextual hate speech words within social media

Social media platforms have recently seen an increase in the occurrence ...
12/03/2021

HS-BAN: A Benchmark Dataset of Social Media Comments for Hate Speech Detection in Bangla

In this paper, we present HS-BAN, a binary class hate speech (HS) datase...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.