Comparison of Machine Learning and Sentiment Analysis in Detection of Suspicious Online Reviewers on Different Type of Data

The article focuses on solving an important problem of detecting suspicious reviewers in online discussions on social networks. We have concentrated on a special type of suspicious authors, on trolls. We have used methods of machine learning for generation of detection models to discriminate a troll...

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Detalles Bibliográficos
Autores principales: Machova, Kristina, Mach, Marian, Vasilko, Matej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747373/
https://www.ncbi.nlm.nih.gov/pubmed/35009698
http://dx.doi.org/10.3390/s22010155

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747373/
https://www.ncbi.nlm.nih.gov/pubmed/35009698
http://dx.doi.org/10.3390/s22010155

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