# Mining Reasons For And Against Vaccination From Unstructured Data Using Nichesourcing and AI Data Augmentation

arXiv: https://arxiv.org/abs/2406.19951 · HTML: https://mlsanity.com/paper/2406.19951/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 21 references that are in the map.
- First posted on arXiv 28 Jun 2024.

## Builds on (most cited first, 7 of 7)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Longformer: The Long-Document Transformer](https://mlsanity.com/paper/2004.05150/) (2020)
- [Spanish Pre-trained BERT Model and Evaluation Data](https://mlsanity.com/paper/2308.02976/) (2023)
- [TextDescriptives: A Python package for calculating a large variety of metrics from text](https://mlsanity.com/paper/2301.02057/) (2023)
- [Which Argumentative Aspects of Hate Speech in Social Media can be reliably identified?](https://mlsanity.com/paper/2306.02978/) (2023)

## Built on by (most cited first, 1 of 1)

- [Utilising Large Language Models for Generating Effective Counter Arguments to Anti-Vaccine Tweets](https://mlsanity.com/paper/2510.16359/) (2025)

## Abstract (arXiv)

We present Reasons For and Against Vaccination (RFAV), a dataset for predicting reasons for and against vaccination, and scientific authorities used to justify them, annotated through nichesourcing and augmented using GPT4 and GPT3.5-Turbo. We show how it is possible to mine these reasons in non-structured text, under different task definitions, despite the high level of subjectivity involved and explore the impact of artificially augmented data using in-context learning with GPT4 and GPT3.5-Turbo. We publish the dataset and the trained models along with the annotation manual used to train annotators and define the task.