Deep Learning students tackle online hate speech - Poster Session on 28 May

Students in the Deep Learning course will showcase their group projects focused on fostering safer online spaces. The poster session will highlight their deep learning models designed to identify and address hate speech across a variety of online content.

The group projects tackle online hate in its diverse forms, ranging from text to images, memes, videos, and audio content. With the objective of creating healthier online interactions, the students designed their models to prioritize both accuracy and a nuanced understanding of context in order to distinguish between genuinely harmful hate speech and legitimate critical discourse or satirical expression.

The development of these deep learning models aims to prevent the proliferation of hateful rhetoric, ultimately contributing to a more respectful online environment where diverse voices can coexist and thrive.