Abstract
While the world has been combating COVID, there has also been an ongoing “Infodemic,” caused by the spread of fake news about the pandemic. Due to the rapid data sharing on social media, the impact of fake news can be quite damaging. Citizens might mistake fakes news for real news. Human lives have been lost due to fake information about COVID. Our goal is to identify fake news on social media and help stem the spread by deep learning approaches. To understand the different characteristics in fake and real news, we conducted behavioral and sentiment analyses between fake and real news regarding the COVID pandemic. We then further built detection models based on feature elimination, and we identified differences of model robustness based on selected features.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
