Identifying Fake News and Postings in Online Social Media


Identifying Fake News and Postings in Online Social Media


With the easy accessibility of Internet connectivity, online social media such as Facebook, Twitter are great sources to disseminate information. Often common citizens can reach an incident site before a news agency does or witness the incident first hand, and report directly in social media. However, recently social media has been engulfed with fake messages and postings such as fake ‘like’ or ‘comment’. There is ample evidence that many Twitter and Facebook accounts spread hoaxes and unconfirmed information as 'BREAKING NEWS!’ This may create social conflict, tarnish business image or even jeopardise an individual’s or a group’s safety, defeating the very cause of Internet's birth to use information for peace and human rights. Though some works have been done in literature for automatic detection of fake news in online social media, currently they fail to achieve the desired level of detection accuracy within a reasonable time. This project will use a combination of machine learning, natural language processing and opinion formation dynamics in social networks. It will be built upon the supervisory team’s recent works on machine learning, and understanding opinion and trust formation among users in social networks. The outcome of the project is likely to attract commercial interest.

Supervisory Team

Principal Supervisor: Prof Joarder Kamruzzaman


Dr Gour Karmakar

Dr Sally Firmin

Dr Tanveer Chowdhury