CoVaxFrames includes 113 Vaccine Hesitancy Framings found on Twitter about the COVID-19 vaccines. Language experts annotated tweets as Relevant or Not Relevant, and then further annotated Relevant tweets with Stance towards each framing.
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CoVaxLies v2 includes 47 Misinformation Targets (MisTs) found on Twitter about the COVID-19 vaccines. Language experts annotated tweets as Relevant or Not Relevant, and then further annotated Relevant tweets with Stance towards each MisT. This collection is a first step in providing large-scale resources for misinformation detection and misinformation stance identification.
HpVaxFrames includes 64 Vaccine Hesitancy Framings found on Twitter about the HPV vaccines. Language experts annotated tweets as Relevant or Not Relevant, and then further annotated Relevant tweets with Stance towards each framing.
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MMVax-Stance includes 113 Vaccine Hesitancy Framings found on Twitter about the COVID-19 vaccines. Language experts annotated multimodal image-text tweets as Relevant or Not Relevant, and then further annotated Relevant tweets with Stance towards each framing.
Combines CoVaxFrames and HpVaxFrames into a unified dataset of 113 Vaccine Hesitancy Framings found on Twitter about the COVID-19 vaccines and 64 Vaccine Hesitancy Framings found on Twitter about the HPV vaccines. Language experts annotated tweets as Relevant or Not Relevant, and then further annotated Relevant tweets with Stance towards each framing.
A Natural Language Resource for Learning to Recognize Misinformation about the COVID-19 and HPV Vaccines.