Misinformation Concierge: A Proof-of-Concept with Curated Twitter Dataset on COVID-19 Vaccination

TL;DR

This paper introduces Misinformation Concierge, a system that leverages NLP and machine learning to identify, analyze, and counter COVID-19 misinformation on Twitter, aiding policymakers with timely insights and rebuttal strategies.

Contribution

It presents a novel proof-of-concept system that combines data analysis, misinformation detection, and intervention recommendations using social media data.

Findings

Effective identification of misinformation subtopics

Generation of statistical reports for policymakers

Provision of rebuttal messages for misinformation

Abstract

We demonstrate the Misinformation Concierge, a proof-of-concept that provides actionable intelligence on misinformation prevalent in social media. Specifically, it uses language processing and machine learning tools to identify subtopics of discourse and discern non/misleading posts; presents statistical reports for policy-makers to understand the big picture of prevalent misinformation in a timely manner; and recommends rebuttal messages for specific pieces of misinformation, identified from within the corpus of data - providing means to intervene and counter misinformation promptly. The Misinformation Concierge proof-of-concept using a curated dataset is accessible at: https://demo-frontend-uy34.onrender.com/