This project seeks to apply and/or advance the state of the art in computer science in the detection and prevention of use of information technology for racist purposes. The project may involve basic research, applied research or a combination of both. It is likely that existing methods addressing other online threats will be relevant to the problem domain including methods to address online misogyny, bullying, terrorist networks and their identification and disruption (as examples). The project is likely to involve use of natural language processing, machine learning and network analysis as existing technologies deployed in this problem domain.
The project may involve working with government and non-government external stakeholders concerned with the problem of online racism to assist them in responding to online racism. Research by publication is encouraged as part of this project.
- Develop technologies that support the best in humanity and challenge the worst
- So the web really is a public good that puts people first.
Requiem for online harassers: Identifying racism from political tweetshttps://ieeexplore.ieee.org/abstract/document/7962526
Multilingual Cross-domain Perspectives on Online Hate Speech https://arxiv.org/ftp/arxiv/papers/1809/1809.03944.pdf
Platformed racism: The mediation and circulation of an Australian race-based controversy on Twitter, Facebook and YouTubehttp://eprints.qut.edu.au/101370/
Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
Platformed racism: The mediation and circulation of an Australian race-based controversy on Twitter, Facebook and YouTube | QUT ePrints
A Unified Deep Learning Architecture for Abuse Detectionhttps://arxiv.org/abs/1802.00385
Deep Learning for Hate Speech Detection in Tweets https://dl.acm.org/citation.cfm?id=3054223
Cyberbullying Detection and Classification Using Information Retrieval Algorithmhttps://dl.acm.org/citation.cfm?id=2743085
Social media and digital technology use among Indigenous young people in Australia: a literature review https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881203/