Round Corner
Department of Computer and Information Science


Identifying Online Hate Speech and Cyber Bullying

During the Spring of 2017, parliamentary committees in Germany and the UK strongly criticised leading social media sites such as Facebook, Twitter and Youtube for failing to take sufficient and quick enough action against hate-speech, with the German government threatening to fine the social networks up to 50 million euros if they continue to fail to remove hateful postings within a week.
With legislation in other countries set to follow, properly identifying hatespeech is a pressing issue, not only for the major players, but also for smaller companies, clubs, and organisations that allow for user-generated content on their sites. Many such sites currently use slow, manual moderation, which mean that abusive posts will be left online for too long without appropriate action being taken or that content will be published with delay (which might be unacceptable to the users, e.g., in online chat rooms).

The thesis project would look into previous efforts to identify hate speech and cyber bullying, as well as available flame-annotated datasets from chat rooms, online games, Wikipedia and Twitter, and investigate various machine learning methods to identify such language.


Björn Gambäck Björn Gambäck
315 IT-bygget
735 93354 
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