IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i17p4802-d263563.html
   My bibliography  Save this article

Detection of Fake Reviews: Analysis of Sellers’ Manipulation Behavior

Author

Listed:
  • Lirong Chen

    (Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China
    School of Computer Science, Inner Mongolia University, Hohhot 010021, China)

  • Wenli Li

    (Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China)

  • Hao Chen

    (School of Business, Qingdao University, Qingdao 266071, China)

  • Shidao Geng

    (School of Maritime Economics and Management, Dalian 116026, China)

Abstract

Online reputation systems play an important role in reducing consumers’ purchase uncertainty in online shopping. However, some sellers manipulate reviews for their own interests, which reduces the effectiveness of the reputation system. Unlike the previous studies, which focus on features of reviews and reviewers, this study establishes a game model to analyze sellers’ manipulation behavior and identifies what kind of sellers or under what scenario sellers are motivated to manipulate reviews. Our study provides a new perspective for platform to detect fake reviews and helps consumers to make good use of online reviews without getting trapped in some sellers’ fraudulent manipulation.

Suggested Citation

  • Lirong Chen & Wenli Li & Hao Chen & Shidao Geng, 2019. "Detection of Fake Reviews: Analysis of Sellers’ Manipulation Behavior," Sustainability, MDPI, vol. 11(17), pages 1-13, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:17:p:4802-:d:263563
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/17/4802/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/17/4802/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jean Tirole, 1988. "The Theory of Industrial Organization," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262200716, April.
    2. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    3. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    4. 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.
    5. Bin Gu & Jaehong Park & Prabhudev Konana, 2012. "Research Note ---The Impact of External Word-of-Mouth Sources on Retailer Sales of High-Involvement Products," Information Systems Research, INFORMS, vol. 23(1), pages 182-196, March.
    6. Dina Mayzlin, 2006. "Promotional Chat on the Internet," Marketing Science, INFORMS, vol. 25(2), pages 155-163, 03-04.
    7. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.
    8. Mikhail I. Melnik & James Alm, 2005. "Seller Reputation, Information Signals, and Prices for Heterogeneous Coins on eBay," Southern Economic Journal, John Wiley & Sons, vol. 72(2), pages 305-328, October.
    9. Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
    10. 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.
    11. Sungjoon Nam & Puneet Manchanda & Pradeep K. Chintagunta, 2010. "The Effect of Signal Quality and Contiguous Word of Mouth on Customer Acquisition for a Video-on-Demand Service," Marketing Science, INFORMS, vol. 29(4), pages 690-700, 07-08.
    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. Katarzyna Sanak-Kosmowska & Jan W. Wiktor, 2020. "Empirical Identification of Latent Classes in the Assessment of Information Asymmetry and Manipulation in Online Advertising," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
    2. Wafa Shafqat & Yung-Cheol Byun, 2019. "A Recommendation Mechanism for Under-Emphasized Tourist Spots Using Topic Modeling and Sentiment Analysis," Sustainability, MDPI, vol. 12(1), pages 1-26, December.
    3. Xueke Du & Rui Dong & Wenli Li & Yibo Jia & Lirong Chen, 2019. "Online Reviews Matter: How Can Platforms Benefit from Online Reviews?," Sustainability, MDPI, vol. 11(22), pages 1-20, November.
    4. Juan Pedro Aznar-Alarcón & Oriol Anguera-Torrell, 2023. "Fake Reviews in Online Platforms and the Effort to Fight Them," Studies in Microeconomics, , vol. 11(2), pages 235-245, August.
    5. Harman Preet Singh & Ibrahim Abdullah Alhamad, 2022. "A Novel Categorization of Key Predictive Factors Impacting Hotels’ Online Ratings: A Case of Makkah," Sustainability, MDPI, vol. 14(24), pages 1-25, December.

    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. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    2. 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).
    3. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.
    4. Young Kwark & Jianqing Chen & Srinivasan Raghunathan, 2014. "Online Product Reviews: Implications for Retailers and Competing Manufacturers," Information Systems Research, INFORMS, vol. 25(1), pages 93-110, March.
    5. Zhang, Tao & Li, Gang & Cheng, T.C.E. & Lai, Kin Keung, 2017. "Welfare economics of review information: Implications for the online selling platform owner," International Journal of Production Economics, Elsevier, vol. 184(C), pages 69-79.
    6. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    7. Peiyu Chen & Lorin M. Hitt & Yili Hong & Shinyi Wu, 2021. "Measuring Product Type and Purchase Uncertainty with Online Product Ratings: A Theoretical Model and Empirical Application," Information Systems Research, INFORMS, vol. 32(4), pages 1470-1489, December.
    8. Li Yimeng & Franco Mariuzzo & Nikolaos Korfiatis & Yu Xiong, 2017. "Information Strategies of new Product Introduction in Vertical Markets," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2017-03, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    9. Tao Lu & May Yuan & Chong (Alex) Wang & Xiaoquan (Michael) Zhang, 2022. "Histogram Distortion Bias in Consumer Choices," Management Science, INFORMS, vol. 68(12), pages 8963-8978, December.
    10. Steffen Zimmermann & Philipp Herrmann & Dennis Kundisch & Barrie R. Nault, 2018. "Decomposing the Variance of Consumer Ratings and the Impact on Price and Demand," Information Systems Research, INFORMS, vol. 29(4), pages 984-1002, December.
    11. Sun, Miao & Chen, Jing & Tian, Ye & Yan, Yufei, 2021. "The impact of online reviews in the presence of customer returns," International Journal of Production Economics, Elsevier, vol. 232(C).
    12. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    13. Yabing Jiang & Hong Guo, 2012. "Design of Consumer Review Systems and Product Pricing," Working Papers 12-10, NET Institute.
    14. Weijia (Daisy) Dai & Ginger Jin & Jungmin Lee & Michael Luca, 2018. "Aggregation of consumer ratings: an application to Yelp.com," Quantitative Marketing and Economics (QME), Springer, vol. 16(3), pages 289-339, September.
    15. David Godes, 2017. "Product Policy in Markets with Word-of-Mouth Communication," Management Science, INFORMS, vol. 63(1), pages 267-278, January.
    16. Hongpeng Wang & Rong Du & Jin Li & Weiguo Fan, 2020. "Subdivided or aggregated online review systems: Which is better for online takeaway vendors?," Electronic Commerce Research, Springer, vol. 20(4), pages 915-944, December.
    17. 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.
    18. Marchand, André & Hennig-Thurau, Thorsten & Wiertz, Caroline, 2017. "Not all digital word of mouth is created equal: Understanding the respective impact of consumer reviews and microblogs on new product success," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 336-354.
    19. 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.
    20. Floyd, Kristopher & Freling, Ryan & Alhoqail, Saad & Cho, Hyun Young & Freling, Traci, 2014. "How Online Product Reviews Affect Retail Sales: A Meta-analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 217-232.

    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:gam:jsusta:v:11:y:2019:i:17:p:4802-:d:263563. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.