资源分类
》 资源 》论文》Hatebusters: A Web Application for Actively Reporting YouTube Hate Speech

Hatebusters: A Web Application for Actively Reporting YouTube Hate Speech

2019-11-06 | |  78 |   49 |   0
Abstract Hatebusters is a web application for actively reporting YouTube hate speech, aiming to establish an online community of volunteer citizens. Hatebusters searches YouTube for videos with potentially hateful comments, scores their comments with a classifier trained on human-annotated data and presents users those comments with the highest probability of being hate speech. It also employs gamification elements, such as achievements and leaderboards, to drive user engagement.

上一篇：Algorithmic Social Intervention Bryan Wilder

下一篇：Repairing ASR output by Artificial Development and Ontology based Learning

用户评价
全部评价

热门资源

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Learning to Predi...

    Much of model-based reinforcement learning invo...