AIRC Team

Research into Fake News online has shown that it can travel faster than real news (Vosoughi et al. 2018), and observation and the media have told us that this type of content is having various effects on our lives. In this project we aim to detect Fake News at its source, without having to wait for the “lie” to “run around the world”. If we can develop machine learning-based techniques that use Natural Language Processing, we can look at the text of the news itself, and determine whether or not it is ‘fake’. In this project, we’ll investigate existing solutions to Automated Fake News Detection problems. With this, we acknowledge that Fake News is a fluid concept, and one that spans many fields: it’s not up to us as computer scientists to decide what truth is, or what news is for that matter. We’ll turn to field experts for advice on fact-checking techniques, and keep ethical concerns like freedom of speech and censorship at top of mind. I have a background in Linguistics and Technical Writing, and have worked for a few large technology companies during my time in industry. I want to make the internet a safer, more trustworthy place, and give people the information they need when they need it.