Evaluating automatic annotation of lexicon-based models for stance detection of M-pox tweets from May 1st to Sep 5th, 2022.

Manually labeling data for supervised learning is time and energy consuming; therefore, lexicon-based models such as VADER and TextBlob are used to automatically label data. However, it is argued that automated labels do not have the accuracy required for training an efficient model. Although automa...

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Detalhes bibliográficos

Principais autores:	Nicholas Perikli, Srimoy Bhattacharya, Blessing Ogbuokiri, Zahra Movahedi Nia, Benjamin Lieberman, Nidhi Tripathi, Salah-Eddine Dahbi, Finn Stevenson, Nicola Bragazzi, Jude Kong, Bruce Mellado
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Public Library of Science (PLoS) 2024-07-01
coleção:	PLOS Digital Health
Acesso em linha:	https://doi.org/10.1371/journal.pdig.0000545
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