Cargando…
Tweet sentiment quantification: An experimental re-evaluation
Sentiment quantification is the task of training, by means of supervised learning, estimators of the relative frequency (also called “prevalence”) of sentiment-related classes (such as Positive, Neutral, Negative) in a sample of unlabelled texts. This task is especially important when these texts ar...
Autores principales: | Moreo, Alejandro, Sebastiani, Fabrizio |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481048/ https://www.ncbi.nlm.nih.gov/pubmed/36112639 http://dx.doi.org/10.1371/journal.pone.0263449 |
Ejemplares similares
-
Sentimental study of CAA by location-based tweets
por: Vashisht, Geetika, et al.
Publicado: (2021) -
A BERT Framework to Sentiment Analysis of Tweets
por: Bello, Abayomi, et al.
Publicado: (2023) -
The Painful Tweet: Text, Sentiment, and Community Structure Analyses of Tweets Pertaining to Pain
por: Tighe, Patrick J, et al.
Publicado: (2015) -
Online Influence and Sentiment of Fitness Tweets: Analysis of Two Million Fitness Tweets
por: Vickey, Theodore, et al.
Publicado: (2017) -
Data on sentiments and emotions of olympic-themed tweets
por: Vertalka, Joshua J., et al.
Publicado: (2019)