MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation

Abstract

The COVID-19 epidemic is considered as the global health crisis of the whole society and the greatest challenge mankind faced since World War Two. Unfortunately, the fake news about COVID-19 is spreading as fast as the virus itself. The incorrect health measurements, anxiety, and hate speeches will have bad consequences on people's physical health, as well as their mental health in the whole world. To help better combat the COVID-19 fake news, we propose a new fake news detection dataset MM-COVID(Multilingual and Multidimensional COVID-19 Fake News Data Repository). This dataset provides the multilingual fake news and the relevant social context. We collect 3981 pieces of fake news content and 7192 trustworthy information from English, Spanish, Portuguese, Hindi, French and Italian, 6 different languages. We present a detailed and exploratory analysis of MM-COVID from different perspectives and demonstrate the utility of MM-COVID in several potential applications of COVID-19 fake news study on multilingual and social media.

References in corpus (5)

• Fake News Detection on Social Media: A Data Mining Perspective
• Cross-lingual Zero- and Few-shot Hate Speech Detection Utilising Frozen Transformer Language Models and AXEL
• Characterizing COVID-19 Misinformation Communities Using a Novel Twitter Dataset
• The Role of User Profile for Fake News Detection
• A curated collection of COVID-19 online datasets

Cited by in corpus (7)

• Memory-Guided Multi-View Multi-Domain Fake News Detection
• Transformer based Automatic COVID-19 Fake News Detection System
• "This is Fake! Shared it by Mistake": Assessing the Intent of Fake News Spreaders
• Dataset of Fake News Detection and Fact Verification: A Survey
• Checkovid: A COVID-19 misinformation detection system on Twitter using network and content mining perspectives
• Challenges and Considerations with Code-Mixed NLP for Multilingual Societies
• Cross-lingual COVID-19 Fake News Detection