Artículos relacionados a Sentiment Analysis of Covid-19 Tweets Using Machine...

Sentiment Analysis of Covid-19 Tweets Using Machine Learning Algorithm - Tapa blanda

Dip, Ahmed Rasidun Bari; Sadik, Md.Shihab; Rozario, Omi Evance

 
9786208118105: Sentiment Analysis of Covid-19 Tweets Using Machine Learning Algorithm
Tapa blanda
ISBN 10: 6208118107 ISBN 13: 9786208118105
Editorial: LAP LAMBERT Academic Publishing, 2024

Sinopsis

Main theme: This article demonstrates that, among a large number of prediction models, the Facebook Prophet Model had the highest accuracy when it came to anticipating pandemic circumstances.Result Analysis: They presented how the models performed on the test sets using the regression and time series models, as well as the analysis using Facebook Prophet. They can calculate the Root Mean Square Error (RMSE) for each model using these results. The comparison of the models based on their RMSE scores is shown in Table I. Table I indicates that when forecasting confirmed instances, the FPM has the lowest average error. Second place goes to the ARIMA model, which is followed by the AR and MA models. However, because the ARIMA incorporates both the MA and AR models, they are not taken into account.The HWA model, which comes after these two, has the lowest score, followed by the PR. Table I shows that the findings are almost identical to the table confirmed cases results, with the FPM coming out on top, followed by the ARIMA, HWA, and PR, in that order. As a result, they come to the conclusion that the best models for anticipating the pandemic situation are as follows: Facebook.

"Sinopsis" puede pertenecer a otra edición de este libro.

Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2024
Idioma
Inglés
ISBN 10 
6208118107
ISBN 13 
9786208118105
Encuadernación
Tapa blanda
Número de páginas
52
Contacto del fabricante
no disponible
Persona responsable
no disponible