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Estimating deception in consumer reviews based on extreme terms: Comparison analysis of open vs. closed hotel reservation platforms

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  • Moon, Sangkil
  • Kim, Moon-Yong
  • Bergey, Paul K.

Abstract

We examine how open and closed review posting policies play differentiating roles in creating social media bias. As a supplementary method to existing ones detecting fake reviews, we develop a trust measure estimating how genuine the review is, based on the frequent usage of strongly positive or negative words. Using the hotel industry as our application context, we empirically demonstrate that our trust measure serves as a correction factor that reduces social media bias. Interestingly, we observe particular hotel service features revealing strong upward manipulation to promote the businesses (for example, positive overall recommendation, interesting surroundings, and personal travel). By contrast, we identify some other features that reveal the presence of strong downward manipulation (for example, negative overall recommendation, disappointing room amenities, and poor atmosphere). From a practical perspective, this research can help both managers and consumers make better informed decisions by reducing the impact attributable to social media manipulation.

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  • Moon, Sangkil & Kim, Moon-Yong & Bergey, Paul K., 2019. "Estimating deception in consumer reviews based on extreme terms: Comparison analysis of open vs. closed hotel reservation platforms," Journal of Business Research, Elsevier, vol. 102(C), pages 83-96.
  • Handle: RePEc:eee:jbrese:v:102:y:2019:i:c:p:83-96
    DOI: 10.1016/j.jbusres.2019.05.016
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    Cited by:

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    4. Kim, Molan & Lee, Seung Min & Choi, Sanghak & Kim, Sang Yong, 2021. "Impact of visual information on online consumer review behavior: Evidence from a hotel booking website," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    5. Ampadu, Seth & Jiang, Yuanchun & Debrah, Emmanuel & Antwi, Collins Opoku & Amankwa, Eric & Gyamfi, Samuel Adu & Amoako, Richard, 2022. "Online personalized recommended product quality and e-impulse buying: A conditional mediation analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    6. Nilashi, Mehrbakhsh & Abumalloh, Rabab Ali & Samad, Sarminah & Alrizq, Mesfer & Alyami, Sultan & Alghamdi, Abdullah, 2023. "Analysis of customers' satisfaction with baby products: The moderating role of brand image," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
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    8. Costa Filho, Murilo & Nogueira Rafael, Diego & Salmonson Guimarães Barros, Lucia & Mesquita, Eduardo, 2023. "Mind the fake reviews! Protecting consumers from deception through persuasion knowledge acquisition," Journal of Business Research, Elsevier, vol. 156(C).
    9. Nilashi, Mehrbakhsh & Abumalloh, Rabab Ali & Minaei-Bidgoli, Behrouz & Abdu Zogaan, Waleed & Alhargan, Ashwaq & Mohd, Saidatulakmal & Syed Azhar, Sharifah Nurlaili Farhana & Asadi, Shahla & Samad, Sar, 2022. "Revealing travellers’ satisfaction during COVID-19 outbreak: Moderating role of service quality," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
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    11. Harrison-Walker, L. Jean & Jiang, Ying, 2023. "Suspicion of online product reviews as fake: Cues and consequences," Journal of Business Research, Elsevier, vol. 160(C).
    12. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "Fake review detection in e-Commerce platforms using aspect-based sentiment analysis," Journal of Business Research, Elsevier, vol. 167(C).

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