Preventhate.org | Policyinstitute.net Algorithms,Society How to Detect Online Hate towards Migrants and Refugees? Developing and Evaluating a Classifier of Racist and Xenophobic Hate Speech Using Shallow and Deep Learning (ideas.repec.org)

How to Detect Online Hate towards Migrants and Refugees? Developing and Evaluating a Classifier of Racist and Xenophobic Hate Speech Using Shallow and Deep Learning (ideas.repec.org)

“First, various traditional shallow learning algorithms are used. Second, deep learning is used, specifically, an ad hoc developed RNN model. Finally, a BERT-based model is developed in which transformers and neural networks are used. The results confirm that deep learning strategies perform better in detecting anti-immigration hate speech online. It is for this reason that the deep architectures were the ones finally improved and tested for hate speech detection in Greek and Italian and in multisource. The results of this study represent an advance in the scientific literature in this field of research, since up to now, no online anti-immigration hate detectors had been tested in these languages and using this type of deep architecture.”

https://ideas.repec.org/a/gam/jsusta/v14y2022i20p13094-d940620.html

Leave a Reply

Your email address will not be published. Required fields are marked *

Related Post

%d bloggers like this: