<strong>Classifier of topic discussed in vaccine-related content in Italian language</strong></br> A monolingual model for classifying the topic discussed in vaccine-related content in Italian language. The model was trained on 36,722 and independently tested on 9,299 social media content between Facebook posts, Twitter tweets, Instagram media and YouTube videos. It is a fine-tuned version of bert-base-multilingual-cased.

<strong>Model output</strong></br> The model classifies each input into one of six distinct classes:</br> <ul> <li>Administration of vaccines</li> <li>Vaccine business</li> <li>Effectiveness of vaccination</li> <li>Legal issues</li> <li>Safety concerns</li> <li>Other</li> </ul>

<strong>Citation info and BibTeX entry</strong></br>

<a href="https://arxiv.org/abs/2207.12264" target="_blank">https://arxiv.org/abs/2207.12264</a>

@article{Bru2022,
  title={Dynamics of (mis)information flow and engaging power of narratives},
  author={Brugnoli, Emanuele and Delmastro, Marco},
  journal={ArXiv},
  year={2022},
  volume={abs/2207.12264}
}