Identifying High Quality Training Data for Misinformation Detection

This paper presents an analysis of different methods for collecting training data in order to train a machine learning classifier for misinformation detection.

Investigating Scientific Misinformation Using Different Modes of Learning

This paper presents an initial analysis of scientific misinformation from research papers.

Detecting and Understanding of Information Pollution on Social Media

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 …

DeMis: Data-efficient Misinformation Detection using Reinforcement Learning

We propose a novel reinforcement learning framework for misinformation detection on Twitter. We release both code, data and pre-trained models.

Misinformation Detection Datasets

More resources are coming soon

Research note: Lies and presidential debates: How political misinformation spread across media streams during the 2020 election

We analyze misinformation about the US 2020 presidential election. We release both data and code including interactive visualizations.

Understanding high-and low-quality URL Sharing on COVID-19 Twitter streams

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 …

A first look at COVID-19 information and misinformation sharing on Twitter

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 …