This paper presents an analysis of different methods for collecting training data in order to train a machine learning classifier for misinformation detection.
This paper presents an initial analysis of scientific misinformation from research papers.
Social media and the web have become primary sources for obtaining information and news. Given the speed and spread of information on social media, effects of poor-quality information, especially with respect to health-related information, can be …
We propose a novel reinforcement learning framework for misinformation detection on Twitter. We release both code, data and pre-trained models.
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We analyze misinformation about the US 2020 presidential election. We release both data and code including interactive visualizations.
This article investigates the prevalence of high and low quality URLs shared on Twitter when users discuss COVID-19. We distinguish between high quality health sources, traditional news sources, and low quality misinformation sources. We find that …
Since December 2019, COVID-19 has been spreading rapidly across the world. Not surprisingly, conversation about COVID-19 is also increasing. This article is a first look at the amount of conversation taking place on social media, specifically …