Project Abstract

With online discourse and harmful content becoming more prevalent with the rise of hate speech, fake news, and extremist content, it is explored how effective it is to remove content from social media platforms for the wider benefit of the user base, as well as the repercussions of automating this process.The aim of this work is to create a simulated environment where different strategies for content removal and content flagging can be explored. The strategies will include AI methods such as rule-based systems, machine learning and combinations of the these. The definition of what classifies as harmful content can vary from person to person, so by being diverse in the design of this project will allow less unexpected outcomes. The work of this project will also explore the ethical, moral, and legal dimensions of automatically removing content from online platforms. We know that some content needs to be removed from social media, but where is the line drawn as to not infringe on a persons universal human right to free speech.

Keywords: Cyber Security, Machine Learning, Simulation

 Conference Details

Session: Presentation Stream 30 at Presentation Slot 2

Location: GH014 at Wednesday 8th 13:30 – 17:00

Markers: Sofya Lyakhova, Hoang Nga Nguyen

Course: MSc Cyber Security, Masters PG

Future Plans: I’m looking for work