Automatic Twitter Stance Detection on Politically Controversial Issues: A Study on Covid-19’s CPI

  • Patricia D. Santos UFABC
  • Denise H. Goya UFABC

Resumo


Prever o posicionamento de usuários de mídias sociais sobre um tópico tema pode ser desafiador, especialmente para casos não supervisionados. Neste trabalho foram utilizadas postagens retuitadas como elementos de interação dos usuários, para calcular as semelhanças entre os mais ativos dentro de uma discussão. A detecção de posicionamento para esses usuários foi realizada usando técnicas de redução de dimensionalidade e clusterização, modelagem de tópicos usando embeddings contextualizados, e rotulação automática de clusters baseada em termos recorrentes em cada grupo. Esta abordagem produziu um pequeno número de clusters de usuários (entre 2 e 3), com uniformidade na rotulação dos usuários em diferentes bases superior a 98%.

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Publicado
29/11/2021
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SANTOS, Patricia D.; GOYA, Denise H.. Automatic Twitter Stance Detection on Politically Controversial Issues: A Study on Covid-19’s CPI. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 524-535. DOI: https://doi.org/10.5753/eniac.2021.18281.