Fake review identification and utility evaluation model using machine learning

Due to the structural growth of e-commerce platforms, the frequency of exchange of opinions and the number of online reviews of platform participants related to products are increasing. However, given the growth of fake reviews, the corresponding growth in the quality of online reviews seems to be s...

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Autores principales: Choi, Wonil, Nam, Kyungmin, Park, Minwoo, Yang, Seoyi, Hwang, Sangyoon, Oh, Hayoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893788/
https://www.ncbi.nlm.nih.gov/pubmed/36744111
http://dx.doi.org/10.3389/frai.2022.1064371
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author Choi, Wonil
Nam, Kyungmin
Park, Minwoo
Yang, Seoyi
Hwang, Sangyoon
Oh, Hayoung
author_facet Choi, Wonil
Nam, Kyungmin
Park, Minwoo
Yang, Seoyi
Hwang, Sangyoon
Oh, Hayoung
author_sort Choi, Wonil
collection PubMed
description Due to the structural growth of e-commerce platforms, the frequency of exchange of opinions and the number of online reviews of platform participants related to products are increasing. However, given the growth of fake reviews, the corresponding growth in the quality of online reviews seems to be slow, at best. The number of cases of harm to retailers and customers caused by malicious false reviews is steadily increasing every year. In this context, it is becoming difficult for users to determine useful reviews amid a flood of information. As a result, the intrinsic value of online reviews that reduce uncertainty in pre-purchase decisions is blurred, and e-commerce platforms are on the verge of losing credibility and traffic. Through this study, we intend to present solutions related to review filtering and classification by constructing a model for judging the authenticity and usefulness of online reviews using machine learning.
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spelling pubmed-98937882023-02-03 Fake review identification and utility evaluation model using machine learning Choi, Wonil Nam, Kyungmin Park, Minwoo Yang, Seoyi Hwang, Sangyoon Oh, Hayoung Front Artif Intell Artificial Intelligence Due to the structural growth of e-commerce platforms, the frequency of exchange of opinions and the number of online reviews of platform participants related to products are increasing. However, given the growth of fake reviews, the corresponding growth in the quality of online reviews seems to be slow, at best. The number of cases of harm to retailers and customers caused by malicious false reviews is steadily increasing every year. In this context, it is becoming difficult for users to determine useful reviews amid a flood of information. As a result, the intrinsic value of online reviews that reduce uncertainty in pre-purchase decisions is blurred, and e-commerce platforms are on the verge of losing credibility and traffic. Through this study, we intend to present solutions related to review filtering and classification by constructing a model for judging the authenticity and usefulness of online reviews using machine learning. Frontiers Media S.A. 2023-01-19 /pmc/articles/PMC9893788/ /pubmed/36744111 http://dx.doi.org/10.3389/frai.2022.1064371 Text en Copyright © 2023 Choi, Nam, Park, Yang, Hwang and Oh. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Choi, Wonil
Nam, Kyungmin
Park, Minwoo
Yang, Seoyi
Hwang, Sangyoon
Oh, Hayoung
Fake review identification and utility evaluation model using machine learning
title Fake review identification and utility evaluation model using machine learning
title_full Fake review identification and utility evaluation model using machine learning
title_fullStr Fake review identification and utility evaluation model using machine learning
title_full_unstemmed Fake review identification and utility evaluation model using machine learning
title_short Fake review identification and utility evaluation model using machine learning
title_sort fake review identification and utility evaluation model using machine learning
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893788/
https://www.ncbi.nlm.nih.gov/pubmed/36744111
http://dx.doi.org/10.3389/frai.2022.1064371
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