Cargando…
The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review
In the last several decades, electronic word of mouth (eWOM) has been widely used by consumers on different digital platforms to gather feedback about products and services from previous customer behavior. However, this useful information is getting blurred by fake reviews—i.e., reviews that were cr...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924504/ https://www.ncbi.nlm.nih.gov/pubmed/33816872 http://dx.doi.org/10.7717/peerj-cs.219 |
_version_ | 1783659104724582400 |
---|---|
author | Reyes-Menendez, Ana Saura, Jose Ramon Filipe, Ferrão |
author_facet | Reyes-Menendez, Ana Saura, Jose Ramon Filipe, Ferrão |
author_sort | Reyes-Menendez, Ana |
collection | PubMed |
description | In the last several decades, electronic word of mouth (eWOM) has been widely used by consumers on different digital platforms to gather feedback about products and services from previous customer behavior. However, this useful information is getting blurred by fake reviews—i.e., reviews that were created artificially and are thus not representative of real customer opinions. The present study aims to thoroughly investigate the phenomenon of fake online reviews in the tourism sector on social networking and online reviews sites. To this end, we conducted a systematic review of the literature on fake reviews for tourism businesses. Our focus was on previous studies that addressed the following two main topics: (i) tourism (ii) fake reviews. Scientific databases were used to collect relevant literature. The search terms “tourism” and “fake reviews” were applied. The database of Web of Science produced a total of 124 articles and, after the application of different filters following the PRISMA 2009 Flow diagram, the process resulted in the selection of 17 studies. Our results demonstrate that (i) the analysis of fake reviews is interdisciplinary, ranging from Computer Science to Business and Management, (ii) the methods are based on algorithms and sentiment analysis, while other methodologies are rarely used; and (iii) the current and future state of fraudulent detection is based on emotional approaches, semantic analysis and new technologies such as Blockchain. This study also provides helpful strategies to counteract the ubiquity of fake reviews for tourism businesses. |
format | Online Article Text |
id | pubmed-7924504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79245042021-04-02 The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review Reyes-Menendez, Ana Saura, Jose Ramon Filipe, Ferrão PeerJ Comput Sci Human–Computer Interaction In the last several decades, electronic word of mouth (eWOM) has been widely used by consumers on different digital platforms to gather feedback about products and services from previous customer behavior. However, this useful information is getting blurred by fake reviews—i.e., reviews that were created artificially and are thus not representative of real customer opinions. The present study aims to thoroughly investigate the phenomenon of fake online reviews in the tourism sector on social networking and online reviews sites. To this end, we conducted a systematic review of the literature on fake reviews for tourism businesses. Our focus was on previous studies that addressed the following two main topics: (i) tourism (ii) fake reviews. Scientific databases were used to collect relevant literature. The search terms “tourism” and “fake reviews” were applied. The database of Web of Science produced a total of 124 articles and, after the application of different filters following the PRISMA 2009 Flow diagram, the process resulted in the selection of 17 studies. Our results demonstrate that (i) the analysis of fake reviews is interdisciplinary, ranging from Computer Science to Business and Management, (ii) the methods are based on algorithms and sentiment analysis, while other methodologies are rarely used; and (iii) the current and future state of fraudulent detection is based on emotional approaches, semantic analysis and new technologies such as Blockchain. This study also provides helpful strategies to counteract the ubiquity of fake reviews for tourism businesses. PeerJ Inc. 2019-09-23 /pmc/articles/PMC7924504/ /pubmed/33816872 http://dx.doi.org/10.7717/peerj-cs.219 Text en ©2019 Reyes-Menendez et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Human–Computer Interaction Reyes-Menendez, Ana Saura, Jose Ramon Filipe, Ferrão The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review |
title | The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review |
title_full | The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review |
title_fullStr | The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review |
title_full_unstemmed | The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review |
title_short | The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review |
title_sort | importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review |
topic | Human–Computer Interaction |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924504/ https://www.ncbi.nlm.nih.gov/pubmed/33816872 http://dx.doi.org/10.7717/peerj-cs.219 |
work_keys_str_mv | AT reyesmenendezana theimportanceofbehavioraldatatoidentifyonlinefakereviewsfortourismbusinessesasystematicreview AT saurajoseramon theimportanceofbehavioraldatatoidentifyonlinefakereviewsfortourismbusinessesasystematicreview AT filipeferrao theimportanceofbehavioraldatatoidentifyonlinefakereviewsfortourismbusinessesasystematicreview AT reyesmenendezana importanceofbehavioraldatatoidentifyonlinefakereviewsfortourismbusinessesasystematicreview AT saurajoseramon importanceofbehavioraldatatoidentifyonlinefakereviewsfortourismbusinessesasystematicreview AT filipeferrao importanceofbehavioraldatatoidentifyonlinefakereviewsfortourismbusinessesasystematicreview |