preventhate.org | Policyinstitute.net
Averting and Countering Online Hatred.
“First, various traditional shallow learning algorithms are used. Second, deep learning is used, specifically, an ad hoc developed RNN model.…
“In order to detect hate speech, we developed Hierarchical Attention Network (HAN) based and Bidirectional Encoder Representations from Transformer (BERT)…
“This paper focuses on classifying hate speech in social media using multiple deep models that are implemented by integrating recent…
Results revealed that most of the previous studies on hate speech focused on the field of computer science but rarely…
Hate speech and trolling have become synonymous with social media – and this can have a knock-on effect on brand…
Online Hate speech detection has become important with the growth of digital devices, but resources in languages other than English…
Detecting online hate is a complex task, and low-performing models have harmful consequences when used for sensitive applications such as…
This paper describes the development and implementation of an innovative resource, namely the Revised HurtLex Lexicon, in which every headword…
In this paper, we investigate the generalization capabilities of deep learning models to different target groups of hate speech under…
This paper builds on the existing work of United Nations bodies to provide more granular and well-calibrated guidance on the…
In this contemporary world, people use social media tremendously to communicate and have fun with their friends and family. Over…
“It is time-consuming and difcult to manually process and classify massive quantities of text data. However, due to the huge…