The State of Infodemic on Twitter
This addresses the issue of misinformation spread during the COVID-19 pandemic for social media users and platforms, but it appears incremental as it applies existing methods to new data.
The paper tackled the problem of COVID-19 misinformation on Twitter by conducting an exploratory analysis and applying machine learning models to identify misinformation in tweets, but no concrete results or numbers are provided.
Following the wave of misinterpreted, manipulated and malicious information growing on the Internet, the misinformation surrounding COVID-19 has become a paramount issue. In the context of the current COVID-19 pandemic, social media posts and platforms are at risk of rumors and misinformation in the face of the serious uncertainty surrounding the virus itself. At the same time, the uncertainty and new nature of COVID-19 means that other unconfirmed information that may appear "rumored" may be an important indicator of the behavior and impact of this new virus. Twitter, in particular, has taken a center stage in this storm where Covid-19 has been a much talked about subject. We have presented an exploratory analysis of the tweets and the users who are involved in spreading misinformation and then delved into machine learning models and natural language processing techniques to identify if a tweet contains misinformation.