# Accuracy of a large language model in distinguishing anti- and pro-vaccination messages on social media: The case of human papillomavirus vaccination

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/accuracy-of-a-large-language-model-in-distinguishing-anti-and-pro-vaccination/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Soojong Kim,Kwanho Kim,Claire Wonjeong Jo |
| Citations | 13 |
| DOI | 10.1016/j.pmedr.2024.102723 |
| Fields | Medicine,Social Sciences |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1016/j.pmedr.2024.102723 |
| OpenAlex ID | https://openalex.org/W4394934956 |
| PMID | 38659997 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Soojong Kim](https://scholariq.org/researchers/soojong-kim/)

## Paper primary topic

- [Vaccine Coverage and Hesitancy](https://scholariq.org/topics/vaccine-coverage-and-hesitancy/)

## Paper topics

- [Vaccine Coverage and Hesitancy](https://scholariq.org/topics/vaccine-coverage-and-hesitancy/)
- [Cervical Cancer and HPV Research](https://scholariq.org/topics/cervical-cancer-and-hpv-research/)
- [Data-Driven Disease Surveillance](https://scholariq.org/topics/data-driven-disease-surveillance/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.