IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v99y2019icp390-397.html
   My bibliography  Save this article

False advertising or slander? Using location based tweets to assess online rating-reliability

Author

Listed:
  • Poddar, Amit
  • Banerjee, Syagnik
  • Sridhar, Karthik

Abstract

Online reviews have diffused into a large variety of businesses, ranging from physical goods to services. The ubiquity of the reviews and the importance given to them by potential customers makes examining their validity extremely important. While good reviews can boost companies' business, bad reviews can spell their doom. Since online reviews are anonymous, there are cases of both false advertising and slander that can create conflict. In this paper authors provide reasons for online rating bias and demonstrate a way to measure it. Authors mine consumer's location aware tweets from business locations to capture a location's pleasure score and compare the pleasure scores to Yelp ratings to determine how overrated or underrated the venue is. Foursquare and Twitter are mined to extract an emotion score from the location aware tweets using a dictionary called the Affective Norms for English Words (ANEW). Rating biases are found across cities and different types of restaurants and managerial and policy implications discussed.

Suggested Citation

  • Poddar, Amit & Banerjee, Syagnik & Sridhar, Karthik, 2019. "False advertising or slander? Using location based tweets to assess online rating-reliability," Journal of Business Research, Elsevier, vol. 99(C), pages 390-397.
    • Handle: RePEc:eee:jbrese:v:99:y:2019:i:c:p:390-397
    DOI: 10.1016/j.jbusres.2017.08.030
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296317302941
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2017.08.030?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. Michael Luca & Georgios Zervas, 2013. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Harvard Business School Working Papers 14-006, Harvard Business School, revised May 2015.
    2. Sparks, Beverley A. & Browning, Victoria, 2011. "The impact of online reviews on hotel booking intentions and perception of trust," Tourism Management, Elsevier, vol. 32(6), pages 1310-1323.
    3. Justin Malbon, 2013. "Taking Fake Online Consumer Reviews Seriously," Journal of Consumer Policy, Springer, vol. 36(2), pages 139-157, June.
    4. Sarah G. Moore, 2015. "Attitude Predictability and Helpfulness in Online Reviews: The Role of Explained Actions and Reactions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 42(1), pages 30-44.
    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. 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).
    2. Ying, Shiyi & Huang, Youlin & Qian, Lixian & Song, Jinzhu, 2023. "Privacy paradox for location tracking in mobile social networking apps: The perspectives of behavioral reasoning and regulatory focus," Technological Forecasting and Social Change, Elsevier, vol. 190(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. Meek, Stephanie & Wilk, Violetta & Lambert, Claire, 2021. "A big data exploration of the informational and normative influences on the helpfulness of online restaurant reviews," Journal of Business Research, Elsevier, vol. 125(C), pages 354-367.
    2. Chen, Feier & Liu, Stephanie Q. & Mattila, Anna S., 2020. "Bragging and humblebragging in online reviews," Annals of Tourism Research, Elsevier, vol. 80(C).
    3. Sharma, Mahak & Antony, Rose & Sehrawat, Rajat & Cruz, Angel Contreras & Daim, Tugrul U., 2022. "Exploring post-adoption behaviors of e-service users: Evidence from the hospitality sector /online travel services," Technology in Society, Elsevier, vol. 68(C).
    4. Wu, Laurie & Shen, Han & Fan, Alei & Mattila, Anna S., 2017. "The impact of language style on consumers′ reactions to online reviews," Tourism Management, Elsevier, vol. 59(C), pages 590-596.
    5. Book, Laura A. & Tanford, Sarah & Chang, Wen, 2018. "Customer reviews are not always informative: The impact of effortful versus heuristic processing," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 272-280.
    6. Inyoung Chae & Andrew T. Stephen & Yakov Bart & Dai Yao, 2017. "Spillover Effects in Seeded Word-of-Mouth Marketing Campaigns," Marketing Science, INFORMS, vol. 36(1), pages 89-104, January.
    7. Zuo, Wenming & Bai, Weijing & Zhu, Wenfeng & He, Xinming & Qiu, Xinxin, 2022. "Changes in service quality of sharing accommodation: Evidence from airbnb," Technology in Society, Elsevier, vol. 71(C).
    8. Chan, Haksin & Yang, Morgan X. & Zeng, Kevin J., 2022. "Bolstering ratings and reviews systems on multi-sided platforms: A co-creation perspective," Journal of Business Research, Elsevier, vol. 139(C), pages 208-217.
    9. Sonny Rosenthal & Jean Yi Colette Tan & Ting Fang Poh, 2020. "Reputation Cues as Signals in the Sharing Economy," Social Sciences, MDPI, vol. 9(4), pages 1-14, April.
    10. Sparks, Beverley A. & Perkins, Helen E. & Buckley, Ralf, 2013. "Online travel reviews as persuasive communication: The effects of content type, source, and certification logos on consumer behavior," Tourism Management, Elsevier, vol. 39(C), pages 1-9.
    11. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    12. Sparks, Beverley A. & So, Kevin Kam Fung & Bradley, Graham L., 2016. "Responding to negative online reviews: The effects of hotel responses on customer inferences of trust and concern," Tourism Management, Elsevier, vol. 53(C), pages 74-85.
    13. Yuanyuan Guo & Yanqing Wang & Chaoyou Wang, 2019. "Exploring the Salient Attributes of Short-Term Rental Experience: An Analysis of Online Reviews from Chinese Guests," Sustainability, MDPI, vol. 11(16), pages 1-19, August.
    14. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    15. 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.
    16. Sunyoung Hlee & Hanna Lee & Chulmo Koo, 2018. "Hospitality and Tourism Online Review Research: A Systematic Analysis and Heuristic-Systematic Model," Sustainability, MDPI, vol. 10(4), pages 1-27, April.
    17. Amaro, Suzanne & Duarte, Paulo & Henriques, Carla, 2016. "Travelers’ use of social media: A clustering approach," Annals of Tourism Research, Elsevier, vol. 59(C), pages 1-15.
    18. José Alberto Martínez-González & Eduardo Parra-López & Almudena Barrientos-Báez, 2021. "Young Consumers’ Intention to Participate in the Sharing Economy: An Integrated Model," Sustainability, MDPI, vol. 13(1), pages 1-21, January.
    19. Ert, Eyal & Fleischer, Aliza & Magen, Nathan, 2016. "Trust and reputation in the sharing economy: The role of personal photos in Airbnb," Tourism Management, Elsevier, vol. 55(C), pages 62-73.
    20. 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.

    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:99:y:2019:i:c:p:390-397. 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.