Cargando…
SCLAVOEM: hyper parameter optimization approach to predictive modelling of COVID-19 infodemic tweets using smote and classifier vote ensemble
Fake COVID-19 tweets are dangerous since they are misinformative, completely inaccurate, as threatening the efforts for flattening the pandemic curve. Thus, aside the COVID-19 pandemic, dealing with fake news and myths about the virus constitute an infodemic issue, which must be tackled by ensuring...
Autores principales: | Olaleye, Taiwo, Abayomi-Alli, Adebayo, Adesemowo, Kayode, Arogundade, Oluwasefunmi Tale, Misra, Sanjay, Kose, Utku |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922071/ https://www.ncbi.nlm.nih.gov/pubmed/35309597 http://dx.doi.org/10.1007/s00500-022-06940-0 |
Ejemplares similares
-
An ensemble predictive analytics of COVID-19 infodemic tweets using bag of words
por: Olaleye, T.O., et al.
Publicado: (2021) -
An Intelligent Marketspace Mobile Application for Marketing Organic Products
por: Arogundade, Oluwasefunmi ‘Tale, et al.
Publicado: (2020) -
Sentiment analysis of COVID-19 tweets from selected hashtags in Nigeria using VADER and Text Blob analyser
por: Abiola, Odeyinka, et al.
Publicado: (2023) -
SMOTE-CD: SMOTE for compositional data
por: Nguyen, Teo, et al.
Publicado: (2023) -
Tweets don’t vote – Twitter discourse from Wales and England during Brexit
por: Peixoto Gomes, Larissa
Publicado: (2023)