NTR Webinar: Expanding the training data for neural network-based hate speech classification

NTR organizes and hosts scientific webinars on neural networks and invites speakers from all over the world to present their recent work.

On April 19 Ashwin Geet D’Sa, Irina Illina and Dominique Fohr, LORIA, INRIA, CNRS, Université de Lorraine, Nancy, France, presented a technical Zoom webinar on Expanding the Training Data for Neural Network-Based Hate Speech Classification.

About the webinar: 

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 threats 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, colleagues from the Université de Lorraine presented  various solutions explored by participants to expand the training data in order to train a reliable model for hate speech classification.

Slide deck link https://drive.google.com/file/d/101gASU93Fl5N86qRYCSn0Pm1uVJzok_9/view?usp=sharing

Webinar recording: https://youtu.be/iyMe6GYyO-8

Moderator and contact: NTR CEO Nick Mikhailovsky: nickm@ntrlab.com.

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