Machine learning to detect false information related to Covid-19 - Tan, Sven Wei Jie (Nanyang Technological University, 2021)
The outbreak of Coronavirus disease 2019 (COVID-19) have resulted in a global crisis with death tolls surpassing millions and crippling many countries’ economy. Having garnered the world’s attention, COVID-19 has been the topic the media has placed its focus on across the past year. However, this has also led to the spread of false news related to COVID-19 over the Internet. While the intent of spreading such untrue news is unclear, they have mislead many people and is a major source of misunderstanding. Thus, there is a need to differentiate legitimate news from the fabricated ones. This project intends to serve this purpose by designing a Chrome extension that can recognize fake news from online websites. The extension will analyse the content of the websites and display the results to the user. The frontend of the extension includes the User-Interface (UI) design done using JavaScript and HTML languages, while the backend utilizes Postgres Database to record user activities. The extension is hosted on Heroku cloud server.