ArticlePeerJ. Computer science2019
The importance of behavioral data to identify online fake reviews for tourism businesses: a systematic review.
Article in PeerJ. Computer science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Analyzing Online Reviews to Uncover Customer Satisfaction Factors in Indian Cultural Tourism Destinations.Behavioral sciences (Basel, Switzerland) · 2023Article
- The effect of big data technologies usage on social competence.PeerJ. Computer science · 2023Article
- Examining Chinese Users' Feedback Comments on HIV Self-testing Kits From e-Commerce Platforms: Thematic and Content Analysis.Journal of medical Internet research · 2022Article
- Engagement of Government Social Media on Facebook during the COVID-19 Pandemic in Macao.International journal of environmental research and public health · 2021Article
- Spammer group detection and diversification of customers' reviews.PeerJ. Computer science · 2021Article
- Fake news detection: a survey of evaluation datasets.PeerJ. Computer science · 2021Article
- Automatic emotion recognition in healthcare data using supervised machine learning.PeerJ. Computer science · 2021Article
- The Impact of Environmental Social Media Publications on User Satisfaction with and Trust in Tourism Businesses.International journal of environmental research and public health · 2020Article
- Marketing challenges in the #MeToo era: gaining business insights using an exploratory sentiment analysis.Heliyon · 2020Article
- What Drives Volunteers to Accept a Digital Platform That Supports NGO Projects?Frontiers in psychology · 2020Article
- The Effect of Reviewers' Self-Disclosure of Personal Review Record on Consumer Purchase Decisions: An ERPs Investigation.Frontiers in psychology · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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