IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v109y2020icp511-523.html
   My bibliography  Save this article

Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews

Author

Listed:
  • Plotkina, Daria
  • Munzel, Andreas
  • Pallud, Jessie

Abstract

The issue of fake online reviews is increasingly relevant due to the growing importance of online reviews to consumers and the growing frequency of deceptive corporate practices. It is, therefore, necessary to be able to detect fake online reviews. An experiment with 1041 respondents allowed us to create two pools of reviews (fake and truthful) and compare them for psycholinguistic deception cues. The resulting automated tool accounted for review valence and incentive and detected deceptive reviews with 81% accuracy. A follow-up experiment with 407 consumers showed that humans have only a 57% accuracy of detection, even when a deception mindset is activated with information on cues of fake online reviews. Therefore, micro-linguistic automated detection can be used to filter the content of reviewing websites to protect online users. Our independent analysis of reviewing websites confirms the presence of dubious content and, therefore, the need to introduce more sophisticated filtering approaches.

Suggested Citation

  • Plotkina, Daria & Munzel, Andreas & Pallud, Jessie, 2020. "Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews," Journal of Business Research, Elsevier, vol. 109(C), pages 511-523.
    • Handle: RePEc:eee:jbrese:v:109:y:2020:i:c:p:511-523
    DOI: 10.1016/j.jbusres.2018.12.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296318306192
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2018.12.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    2. Plotkina, Daria & Munzel, Andreas, 2016. "Delight the experts, but never dissatisfy your customers! A multi-category study on the effects of online review source on intention to buy a new product," Journal of Retailing and Consumer Services, Elsevier, vol. 29(C), pages 1-11.
    3. Park, Cheol & Lee, Thae Min, 2009. "Information direction, website reputation and eWOM effect: A moderating role of product type," Journal of Business Research, Elsevier, vol. 62(1), pages 61-67, January.
    4. Andreas Munzel, 2016. "Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus," Post-Print hal-02423574, HAL.
    5. Munzel, Andreas, 2016. "Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 96-108.
    6. Friestad, Marian & Wright, Peter, 1994. "The Persuasion Knowledge Model: How People Cope with Persuasion Attempts," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 1-31, June.
    7. L. Kent Marett & Joey F. George, 2004. "Deception in the Case of One Sender and Multiple Receivers," Group Decision and Negotiation, Springer, vol. 13(1), pages 29-44, January.
    8. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    9. Daria Plotkina & Andreas Munzel, 2016. "Delight the experts, but never dissatisfy your customers! A multi-category study on the effects of online review source on intention to buy a new product," Post-Print halshs-01522518, HAL.
    10. Qihua Liu & Shan Huang & Liyi Zhang, 2016. "The influence of information cascades on online purchase behaviors of search and experience products," Electronic Commerce Research, Springer, vol. 16(4), pages 553-580, December.
    11. Dreber, Anna & Johannesson, Magnus, 2008. "Gender differences in deception," Economics Letters, Elsevier, vol. 99(1), pages 197-199, April.
    12. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    13. Justin Malbon, 2013. "Taking Fake Online Consumer Reviews Seriously," Journal of Consumer Policy, Springer, vol. 36(2), pages 139-157, June.
    14. Reimer, Thomas & Benkenstein, Martin, 2016. "When good WOM hurts and bad WOM gains: The effect of untrustworthy online reviews," Journal of Business Research, Elsevier, vol. 69(12), pages 5993-6001.
    15. Daria Plotkina & Andreas Munzel, 2016. "Delight the experts, but never dissatisfy your customers! A multi-category study on the effects of online review source on intention to buy a new product," Post-Print hal-02423571, HAL.
    16. Ketron, Seth, 2017. "Investigating the effect of quality of grammar and mechanics (QGAM) in online reviews: The mediating role of reviewer crediblity," Journal of Business Research, Elsevier, vol. 81(C), pages 51-59.
    17. Theodoros Lappas & Gaurav Sabnis & Georgios Valkanas, 2016. "The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry," Information Systems Research, INFORMS, vol. 27(4), pages 940-961, December.
    18. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    19. Andreas Munzel, 2016. "Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus," Post-Print halshs-01522497, HAL.
    20. Dabholkar, Pratibha A, 1994. "Incorporating Choice into an Attitudinal Framework: Analyzing Models of Mental Comparison Processes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 100-118, June.
    21. Sjaak Hurkens & Navin Kartik, 2009. "Would I lie to you? On social preferences and lying aversion," Experimental Economics, Springer;Economic Science Association, vol. 12(2), pages 180-192, June.
    22. Michael Luca & Georgios Zervas, 2016. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Management Science, INFORMS, vol. 62(12), pages 3412-3427, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Kumar, Ajay & Lu Wang, Cheng & Gupta, Shivam, 2023. "Impacts of consumer cognitive process to ascertain online fake review: A cognitive dissonance theory approach," Journal of Business Research, Elsevier, vol. 154(C).
    2. Banerjee, Snehasish & Chua, Alton Y.K., 2023. "Understanding online fake review production strategies," Journal of Business Research, Elsevier, vol. 156(C).
    3. Josef Zelenka & Tracy Azubuike & Martina Pásková, 2021. "Trust Model for Online Reviews of Tourism Services and Evaluation of Destinations," Administrative Sciences, MDPI, vol. 11(2), pages 1-21, March.
    4. Tim Kollmer & Andreas Eckhardt & Victoria Reibenspiess, 2022. "Explaining consumer suspicion: insights of a vignette study on online product reviews," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1221-1238, September.
    5. Mark Ryan & Josephina Antoniou & Laurence Brooks & Tilimbe Jiya & Kevin Macnish & Bernd Stahl, 2020. "The Ethical Balance of Using Smart Information Systems for Promoting the United Nations’ Sustainable Development Goals," Sustainability, MDPI, vol. 12(12), pages 1-22, June.
    6. Salminen, Joni & Kandpal, Chandrashekhar & Kamel, Ahmed Mohamed & Jung, Soon-gyo & Jansen, Bernard J., 2022. "Creating and detecting fake reviews of online products," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    7. Wu, Ruhai & Qiu, Chun, 2023. "When Karma strikes back: A model of seller manipulation of consumer reviews in an online marketplace," Journal of Business Research, Elsevier, vol. 155(PB).
    8. Hajek, Petr & Sahut, Jean-Michel, 2022. "Mining behavioural and sentiment-dependent linguistic patterns from restaurant reviews for fake review detection," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    9. Zaman, Mustafeed & Vo-Thanh, Tan & Nguyen, Chi T.K. & Hasan, Rajibul & Akter, Shahriar & Mariani, Marcello & Hikkerova, Lubica, 2023. "Motives for posting fake reviews: Evidence from a cross-cultural comparison," Journal of Business Research, Elsevier, vol. 154(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Könsgen, Raoul & Schaarschmidt, Mario & Ivens, Stefan & Munzel, Andreas, 2018. "Finding Meaning in Contradiction on Employee Review Sites — Effects of Discrepant Online Reviews on Job Application Intentions," Journal of Interactive Marketing, Elsevier, vol. 43(C), pages 165-177.
    2. Hui Zhao & Xiaoyuan Wang & Debing Ni & Kevin W. Li, 2023. "The Quality-Signaling Role of Manipulated Consumer Reviews," Group Decision and Negotiation, Springer, vol. 32(3), pages 503-536, June.
    3. Mardumyan, Anna & Siret, Iris, 2023. "When review verification does more harm than good: How certified reviews determine customer–brand relationship quality," Journal of Business Research, Elsevier, vol. 160(C).
    4. Petrescu, Maria & O’Leary, Kathleen & Goldring, Deborah & Ben Mrad, Selima, 2018. "Incentivized reviews: Promising the moon for a few stars," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 288-295.
    5. Moon, Sangkil & Kim, Moon-Yong & Iacobucci, Dawn, 2021. "Content analysis of fake consumer reviews by survey-based text categorization," International Journal of Research in Marketing, Elsevier, vol. 38(2), pages 343-364.
    6. 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).
    7. Perez, Dikla & Stockheim, Inbal & Baratz, Guy, 2022. "Complimentary competition: The impact of positive competitor reviews on review credibility and consumer purchase intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    8. Zhuang, Mengzhou & Cui, Geng & Peng, Ling, 2018. "Manufactured opinions: The effect of manipulating online product reviews," Journal of Business Research, Elsevier, vol. 87(C), pages 24-35.
    9. Koukova, Nevena T. & Wang, Rebecca Jen-Hui & Isaac, Mathew S., 2023. "“If you loved our product”: Do conditional review requests harm retailer loyalty?," Journal of Retailing, Elsevier, vol. 99(1), pages 85-101.
    10. Ismagilova, Elvira & Slade, Emma & Rana, Nripendra P. & Dwivedi, Yogesh K., 2020. "The effect of characteristics of source credibility on consumer behaviour: A meta-analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    11. Birim, Şule Öztürk & Kazancoglu, Ipek & Kumar Mangla, Sachin & Kahraman, Aysun & Kumar, Satish & Kazancoglu, Yigit, 2022. "Detecting fake reviews through topic modelling," Journal of Business Research, Elsevier, vol. 149(C), pages 884-900.
    12. Zheng, Lili, 2021. "The classification of online consumer reviews: A systematic literature review and integrative framework," Journal of Business Research, Elsevier, vol. 135(C), pages 226-251.
    13. Petrescu, Maria & Ajjan, Haya & Harrison, Dana L., 2023. "Man vs machine – Detecting deception in online reviews," Journal of Business Research, Elsevier, vol. 154(C).
    14. Elvira Ismagilova & Emma L. Slade & Nripendra P. Rana & Yogesh K. Dwivedi, 2020. "The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis," Information Systems Frontiers, Springer, vol. 22(5), pages 1203-1226, October.
    15. Ismagilova, Elvira & Dwivedi, Yogesh K. & Slade, Emma, 2020. "Perceived helpfulness of eWOM: Emotions, fairness and rationality," Journal of Retailing and Consumer Services, Elsevier, vol. 53(C).
    16. Guo, Qiaozhen & Chen, Ying-Ju & Huang, Wei, 2022. "Dynamic pricing of new experience products with dual-channel social learning and online review manipulations," Omega, Elsevier, vol. 109(C).
    17. Ayat Zaki Ahmed & Manuel Rodríguez Díaz, 2022. "A Methodology for Machine-Learning Content Analysis to Define the Key Labels in the Titles of Online Customer Reviews with the Rating Evaluation," Sustainability, MDPI, vol. 14(15), pages 1-31, July.
    18. Hossin Md Altab & Mu Yinping & Hosain Md Sajjad & Adasa Nkrumah Kofi Frimpong & Michelle Frempomaa Frempong & Stephen Sarfo Adu-Yeboah, 2022. "Understanding Online Consumer Textual Reviews and Rating: Review Length With Moderated Multiple Regression Analysis Approach," SAGE Open, , vol. 12(2), pages 21582440221, June.
    19. Costa, Ana & Guerreiro, João & Moro, Sérgio & Henriques, Roberto, 2019. "Unfolding the characteristics of incentivized online reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 272-281.
    20. Cheng Zhao & Chong Alex Wang, 2023. "A cross-site comparison of online review manipulation using Benford’s law," Electronic Commerce Research, Springer, vol. 23(1), pages 365-406, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:109:y:2020:i:c:p:511-523. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.