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Detection of Fake News in Online Media


The project is intended to develop an automated textual analytic system to flag and filter inaccurate or false news online. It will identify major features of fake news compared with non-fake news and use them to develop a detection system with the aid of machine learning through a large sample of legitimate and fake news.

Expected deliverable

We are expecting to obtain promising research results: (1) classify the fake news into pre-defined distinct types including the verification of the types of fake news at first. (2) automatically detect the different types of fake news.

A real time detection system is expected to be built up based on the research results for sustainable improvement in different application domains. The final product might include the platforms in different languages, especially in Chinese.

Team members

Prof. Chin Yuk Lun, Dr Paul Lee, Dr Claire Li, Mr. Lap Pong Cheung

Project leader

Dr. Li Wan Yin Claire  Email: :   Tel: 3963 5641


25/07/2017 Topic on Detection of Fake news in Online Media 

15/08/2017 Project Schedule and plan

7/09/2017 Review on Fake News Detection

25/09/2017 Detection of fake news & Review on Fact Checking

09/10/2017 Review on fact checking and automatic fact checking system

16/10/2017 Fact Checking Validating Model-1017

23/10/2017 Factual Claim Validation-1023

30/10/2017 Factual Claim Validation 1031

13/11/2017 Fact-checking sites and Truth Discovery 1113

04/12/2017 on line media features 1204

19/12/2017 Fake news dtection on weibo-1219

16/01/2018Proposed CNN-RNN model for Fake News Detection in on-line media-0116