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CoVerifi: A COVID-19 news verification system
Nikhil L Kolluri1, Dhiraj Murthy2
1Department of Electrical and Computer Engineering, University of Texas, Austin, TX 78712, United States.
Online Social Networks and Media
|February 1, 2021
Summary
The COVID-19 infodemic is combated by CoVerifi, a new web application using machine learning and human feedback to verify news credibility. This tool aims to reduce misinformation and disinformation by enabling user voting and releasing open-source data for further research.
Area of Science:
- Health Informatics
- Computational Social Science
- Information Science
Background:
- The COVID-19 pandemic generated an 'infodemic' of misinformation and disinformation, making it difficult for the public to assess news veracity.
- Vulnerable populations are disproportionately affected by misinformation, leading to stress and societal disruptions like panic buying.
- Existing research-led websites provide valuable accurate information, but new strategies are needed to combat the rapid spread of false news.
Discussion:
- CoVerifi is a novel web application designed to address the COVID-19 infodemic by assessing news credibility.
- It integrates machine learning algorithms with human feedback, allowing users to "vote" on the reliability of news content.
- This crowdsourced approach generates labeled data crucial for training AI models and understanding misinformation patterns.
Key Insights:
- CoVerifi leverages a hybrid approach of AI and human intelligence to evaluate news credibility.
- User engagement through voting provides a scalable method for data collection on misinformation.
- The platform's open-source data release will foster further academic research into combating health-related disinformation.
Outlook:
- CoVerifi has the potential to be deployed at scale to significantly mitigate the impact of the COVID-19 infodemic.
- Future research can build upon the open-source dataset to develop more sophisticated misinformation detection tools.
- The model offers a sustainable solution for maintaining information integrity during public health crises.
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