Спикер о работе:
The phenomenal increase in internet usage, has led to an increase in online hate speech.
Online hate speech is anti-social communicative behavior, which leads to the threat and violence towards an individual or a group.
Deep learning-based models have become the state-of-the-art solution in classifying hate speech. However, the performance of these models depends
on the amount of labeled training data. In this webinar, we present various solutions explored by us to expand the training data to train a reliable model for hate speech classification.
Дополнительные ссылки:
Google Scholar (Ashwin): https://scholar.google.com/citations?user=zN6NAx0AAAAJ&hl=en
Google Scholar (Irina): https://scholar.google.com/citations?user=nLQkiAwAAAAJ&hl=en
Примечание:
Event will be in English
Запись: https://youtu.be/iyMe6GYyO-8
Презентация: https://drive.google.com/file/d/101gASU93Fl5N86qRYCSn0Pm1uVJzok_9/view?usp=sharing