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PoxVerifi: An Information Verification System to Combat Monkeypox Misinformation

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arxiv 2209.09300 v1 pith:JA27CDYE submitted 2022-09-09 cs.CL cs.LGcs.SI

classification cs.CLcs.LGcs.SI
keywords accuracymisinformationmonkeypoxpoxverifiinformationclaimscomprehensivemonkeypox-related
verification ladder T0 review T1 audit T2 compute T3 formal

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Following recent outbreaks, monkeypox-related misinformation continues to rapidly spread online. This negatively impacts response strategies and disproportionately harms LGBTQ+ communities in the short-term, and ultimately undermines the overall effectiveness of public health responses. In an attempt to combat monkeypox-related misinformation, we present PoxVerifi, an open-source, extensible tool that provides a comprehensive approach to assessing the accuracy of monkeypox related claims. Leveraging information from existing fact checking sources and published World Health Organization (WHO) information, we created an open-sourced corpus of 225 rated monkeypox claims. Additionally, we trained an open-sourced BERT-based machine learning model for specifically classifying monkeypox information, which achieved 96% cross-validation accuracy. PoxVerifi is a Google Chrome browser extension designed to empower users to navigate through monkeypox-related misinformation. Specifically, PoxVerifi provides users with a comprehensive toolkit to assess the veracity of headlines on any webpage across the Internet without having to visit an external site. Users can view an automated accuracy review from our trained machine learning model, a user-generated accuracy review based on community-member votes, and have the ability to see similar, vetted, claims. Besides PoxVerifi's comprehensive approach to claim-testing, our platform provides an efficient and accessible method to crowdsource accuracy ratings on monkeypox related-claims, which can be aggregated to create new labeled misinformation datasets.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Dashboard Approach to Monitoring Mpox-Related Discourse and Misinformation on Social Media

    cs.SI 2025-05 conditional novelty 4.0 of 10

    The authors present a Streamlit dashboard for searching and visualizing mpox tweets and claim rising cynical sentiment, without releasing code or data.

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