IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v20y2018i3d10.1007_s10796-016-9697-z.html
   My bibliography  Save this article

Product recommendation with latent review topics

Author

Listed:
  • Juheng Zhang

    (University of Massachusetts)

  • Selwyn Piramuthu

    (University of Florida)

Abstract

Online customer reviews complement information from product and service providers. While the latter is directly from the source of the product and/or service, the former is generally from users of these products and/or services. Clearly, these two information sets are generated from different perspectives with possibly different sets of intentions. For a prospective customer, both these perspectives together provide a complementary set of information and support their purchase decisions. Given the different perspective and incentive structure, the information from these two source sets tends to be necessarily biased, clearly with the high probability of negative information omission from that provided by the product/service providers. Moreover, customers oftentimes face information overload during their attempts at deciphering existing online customer reviews. We attempt to alleviate this through mining hidden information in online customer reviews. We use a variant of the Latent Dirichlet Allocation (LDA) model and clustering to generate equivalent options that the customer could then use in their purchase decisions. We illustrate this using online hotel review data.

Suggested Citation

  • Juheng Zhang & Selwyn Piramuthu, 2018. "Product recommendation with latent review topics," Information Systems Frontiers, Springer, vol. 20(3), pages 617-625, June.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:3:d:10.1007_s10796-016-9697-z
    DOI: 10.1007/s10796-016-9697-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-016-9697-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-016-9697-z?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. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    2. Juheng Zhang & Haldun Aytug & Gary J. Koehler, 2014. "Research Note —Discriminant Analysis with Strategically Manipulated Data," Information Systems Research, INFORMS, vol. 25(3), pages 654-662, September.
    3. Xiangbin Yan & Jing Wang & Michael Chau, 2015. "Customer revisit intention to restaurants: Evidence from online reviews," Information Systems Frontiers, Springer, vol. 17(3), pages 645-657, June.
    4. Piramuthu, Selwyn, 2004. "Evaluating feature selection methods for learning in data mining applications," European Journal of Operational Research, Elsevier, vol. 156(2), pages 483-494, July.
    5. Zhang, Juheng & Aytug, Haldun, 2016. "Comparison of imputation methods for discriminant analysis with strategically hidden data," European Journal of Operational Research, Elsevier, vol. 255(2), pages 522-530.
    6. Selwyn Piramuthu, 1999. "Feature Selection for Financial Credit-Risk Evaluation Decisions," INFORMS Journal on Computing, INFORMS, vol. 11(3), pages 258-266, August.
    7. 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.
    8. Baron David P., 2002. "Private Ordering on the Internet: The EBay Community of Traders," Business and Politics, De Gruyter, vol. 4(3), pages 1-31, November.
    9. Hirshleifer, David & Teoh, Siew Hong, 2003. "Limited attention, information disclosure, and financial reporting," Journal of Accounting and Economics, Elsevier, vol. 36(1-3), pages 337-386, December.
    10. Stephen Burgess & Carmine Sellitto & Carmen Cox & Jeremy Buultjens, 2011. "Trust perceptions of online travel information by different content creators: Some social and legal implications," Information Systems Frontiers, Springer, vol. 13(2), pages 221-235, April.
    11. Baron, David P., 2002. "Private Ordering on the Internet: The eBay Community of Traders," Business and Politics, Cambridge University Press, vol. 4(3), pages 245-274, November.
    12. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    13. Healy, Paul M. & Palepu, Krishna G., 2001. "Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 405-440, September.
    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. Ali M Ahmed Al-Sabaawi & Hacer Karacan & Yusuf Erkan Yenice, 2020. "Exploiting implicit social relationships via dimension reduction to improve recommendation system performance," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-18, April.
    2. Shalak Mendon & Pankaj Dutta & Abhishek Behl & Stefan Lessmann, 2021. "A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters," Information Systems Frontiers, Springer, vol. 23(5), pages 1145-1168, September.
    3. Mohammadreza Mousavizadeh & Mehrdad Koohikamali & Mohammad Salehan & Dam J. Kim, 2022. "An Investigation of Peripheral and Central Cues of Online Customer Review Voting and Helpfulness through the Lens of Elaboration Likelihood Model," Information Systems Frontiers, Springer, vol. 24(1), pages 211-231, February.
    4. Peng Xie, 2022. "The Interplay Between Investor Activity on Virtual Investment Community and the Trading Dynamics: Evidence From the Bitcoin Market," Information Systems Frontiers, Springer, vol. 24(4), pages 1287-1303, August.
    5. Weiwei Deng, 2022. "Leveraging consumer behaviors for product recommendation: an approach based on heterogeneous network," Electronic Commerce Research, Springer, vol. 22(4), pages 1079-1105, December.
    6. Hung-Pin Shih & Pei-Chen Sung, 2021. "Addressing the Review-Based Learning and Private Information Approaches to Foster Platform Continuance," Information Systems Frontiers, Springer, vol. 23(3), pages 649-661, June.
    7. Luvai Motiwalla & Amit V. Deokar & Surendra Sarnikar & Angelika Dimoka, 2019. "Leveraging Data Analytics for Behavioral Research," Information Systems Frontiers, Springer, vol. 21(4), pages 735-742, August.
    8. Yang, Zaoli & Li, Qin & Charles, Vincent & Xu, Bing & Gupta, Shivam, 2023. "Supporting personalized new energy vehicle purchase decision-making: Customer reviews and product recommendation platform," International Journal of Production Economics, Elsevier, vol. 265(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. Juheng Zhang & Selwyn Piramuthu, 0. "Product recommendation with latent review topics," Information Systems Frontiers, Springer, vol. 0, pages 1-9.
    2. Juheng Zhang & Haldun Aytug & Gary J. Koehler, 2014. "Research Note —Discriminant Analysis with Strategically Manipulated Data," Information Systems Research, INFORMS, vol. 25(3), pages 654-662, September.
    3. Eachempati, Prajwal & Srivastava, Praveen Ranjan & Kumar, Ajay & Tan, Kim Hua & Gupta, Shivam, 2021. "Validating the impact of accounting disclosures on stock market: A deep neural network approach," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    4. Annika Wahl & Michel Charifzadeh & Fabian Diefenbach, 2020. "Voluntary Adopters of Integrated Reporting – Evidence on Forecast Accuracy and Firm Value," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2542-2556, September.
    5. Zhang, Juheng & Aytug, Haldun, 2016. "Comparison of imputation methods for discriminant analysis with strategically hidden data," European Journal of Operational Research, Elsevier, vol. 255(2), pages 522-530.
    6. Andrew Ferguson & Tom Scott & Neil Fargher, 2016. "The determinants and market reaction to Open Briefings: an investor relations option and evidence on the effectiveness of disclosure," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 803-843, September.
    7. Ginger Zhe Jin & Andrew Kato & John A. List, 2010. "That’S News To Me! Information Revelation In Professional Certification Markets," Economic Inquiry, Western Economic Association International, vol. 48(1), pages 104-122, January.
    8. Eunsoo Kim & Suyon Kim & Jaehong Lee, 2021. "Do Foreign Investors Affect Carbon Emission Disclosure? Evidence from South Korea," IJERPH, MDPI, vol. 18(19), pages 1-14, September.
    9. Stephen A. Hillegeist & James P. Kavourakis & Matthew Pinnuck, 2023. "The association between quarter length, forecast errors, and firms’ voluntary disclosures," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(2), pages 1885-1918, June.
    10. Florian Meier, 2020. "The Age of Cheap Money and Passive Investing: Are Pro Forma Earnings Value Relevant?," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 9(2), pages 1-1.
    11. Loukil, Nadia & Yousfi, Ouidad, 2010. "Firm's information environment and stock liquidity: evidence from Tunisian context," MPRA Paper 28699, University Library of Munich, Germany, revised Feb 2011.
    12. Patrick Bajari & Ali Hortaçsu, 2004. "Economic Insights from Internet Auctions," Journal of Economic Literature, American Economic Association, vol. 42(2), pages 457-486, June.
    13. Abdo, Hafez & Mangena, Musa & Needham, Graham & Hunt, David, 2018. "Disclosure of provisions for decommissioning costs in annual reports of oil and gas companies: A content analysis and stakeholder views," Accounting forum, Elsevier, vol. 42(4), pages 341-358.
    14. Kim, Jongkyum & Lim, Jee-Hae & Yoon, Kyunghee, 2022. "How do the content, format, and tone of Twitter-based corporate disclosure vary depending on earnings performance?," International Journal of Accounting Information Systems, Elsevier, vol. 47(C).
    15. 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.
    16. Andy Lardon & Marc Deloof, 2014. "Financial disclosure by SMEs listed on a semi-regulated market: evidence from the Euronext Free Market," Small Business Economics, Springer, vol. 42(2), pages 361-385, February.
    17. Olga Plesco & Ludmila Sobol, 2013. "The Issue Of Asymmetric Information Upon The Capital Market," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 5(2), pages 254-266.
    18. Minxing Sun & Weike Xu, 2024. "Short selling and readability in financial disclosures: A controlled experiment," The Financial Review, Eastern Finance Association, vol. 59(2), pages 265-292, May.
    19. B. Charumathi & Latha Ramesh, 2020. "Impact of Voluntary Disclosure on Valuation of Firms: Evidence from Indian Companies," Vision, , vol. 24(2), pages 194-203, June.
    20. Alexander, Cindy R. & Bauguess, Scott W. & Bernile, Gennaro & Lee, Yoon-Ho Alex & Marietta-Westberg, Jennifer, 2013. "Economic effects of SOX Section 404 compliance: A corporate insider perspective," Journal of Accounting and Economics, Elsevier, vol. 56(2), pages 267-290.

    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:spr:infosf:v:20:y:2018:i:3:d:10.1007_s10796-016-9697-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.