Close up of person using mobile phone

Helping Social Media Users Capture and Report Dark Ads

Team: Dannica Batoon, Geordie Elliot-Kerr, Liam King, Muskaan Nagar, and Yuequing Xuan.
Mentor: Dr Danula Hettiachchi 


While everyone sees illegal or dishonest ads, only a very few ever report an ad and get an actual outcome from it. Therefore, this team proposed a simple tool for Australians to report any ad. 

This solution leverages a deep learning ad classification model to triage reports to the relevant body and grade them in terms of severity to allow for rapid dishonest ad removal.

The app will work across platforms through web extensions, and mobile apps and provide constant updates to users on their reports.


Credit: Dannica Batoon, Geordie Elliot-Kerr, Liam King, Muskaan Nagar, Yuequing Xuan and Dr Danula Hettiachchi .

Suggested Citation: Batoon, D., Elliot-Kerr, G., King, L., Nagar, M., Xuan, Y. & Hettiachchi, D. (2022). Tech for Good: ADM+S Dark Ads Hackathon. Helping social media users capture and report dark ads. Australian Research Council Centre for Automated Decision-Making and Society.


If you are interested in collaborating on this research or speaking with this hackathon team contact