IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v129y2024ics0305048324001269.html
   My bibliography  Save this article

Online commodity recommendation model for interaction between user ratings and intensity-weighted hierarchical sentiment: A case study of LYCOM

Author

Listed:
  • Zhang, Chonghui
  • Zhang, Na
  • Su, Weihua
  • Balezentis, Tomas

Abstract

The online commodity recommendation (OCR) model mines users’ historical behavior characteristics and recommends products that may be of interest according to user preferences. Online reviews are among the most important information sources for OCR. However, the explicit and implicit emotional words in online review texts have different structures in the expression of multi-attribute emotions. To fully utilize review information and improve the recommendation accuracy, we propose an OCR model that considers the interaction of multiple attributes and hierarchical emotions and calculates a score weighted by emotion intensity. First, to balance the efficiency and accuracy of information extraction while considering the coexistence of explicit and implicit expressions in online review text, a multi-attribute hierarchical emotion lexicon construction method is proposed. Second, based on the advantage of intuitionistic fuzzy sets in terms of information expression superiority, multi-attribute review text information expression of the affective polarity and intensity of online review text is realized. Then, combined with the weighted singular value decomposition and factorization machine method, we propose an OCR model for interactions between multi-attribute emotions and scores through fusion and recombination of the eigenvectors of users and products. Finally, tourism products on the LYCOM website are used as an example to verify the effectiveness of the proposed method.

Suggested Citation

  • Zhang, Chonghui & Zhang, Na & Su, Weihua & Balezentis, Tomas, 2024. "Online commodity recommendation model for interaction between user ratings and intensity-weighted hierarchical sentiment: A case study of LYCOM," Omega, Elsevier, vol. 129(C).
    • Handle: RePEc:eee:jomega:v:129:y:2024:i:c:s0305048324001269
    DOI: 10.1016/j.omega.2024.103161
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048324001269
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2024.103161?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. Park, Jaehun & Lee, Byung Kwon, 2021. "An opinion-driven decision-support framework for benchmarking hotel service," Omega, Elsevier, vol. 103(C).
    2. Li, Hengyun & Hu, Mingming & Li, Gang, 2020. "Forecasting tourism demand with multisource big data," Annals of Tourism Research, Elsevier, vol. 83(C).
    3. Díaz, Raymundo & Fernández, Eduardo & Figueira, José-Rui & Navarro, Jorge & Solares, Efrain, 2023. "A new hierarchical multiple criteria ordered clustering approach as a complementary tool for sorting and ranking problems," Omega, Elsevier, vol. 117(C).
    4. Gao, Baojun & Li, Xiangge & Liu, Shan & Fang, Debin, 2018. "How power distance affects online hotel ratings: The positive moderating roles of hotel chain and reviewers’ travel experience," Tourism Management, Elsevier, vol. 65(C), pages 176-186.
    5. 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).
    6. Liu, Fan & Liao, Huchang & Al-Barakati, Abdullah, 2023. "Physician selection based on user-generated content considering interactive criteria and risk preferences of patients," Omega, Elsevier, vol. 115(C).
    7. Jia-Li Chang & Hui Li & Jian-Wu Bi, 2022. "Personalized travel recommendation: a hybrid method with collaborative filtering and social network analysis," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(14), pages 2338-2356, July.
    8. Li, Hui & Wu, Dongdong, 2024. "Online investor attention and firm restructuring performance: Insights from an event-based DEA-Tobit model," Omega, Elsevier, vol. 122(C).
    9. Yu, Joanne & Egger, Roman, 2021. "Color and engagement in touristic Instagram pictures: A machine learning approach," Annals of Tourism Research, Elsevier, vol. 89(C).
    10. Heidary Dahooie, Jalil & Raafat, Romina & Qorbani, Ali Reza & Daim, Tugrul, 2021. "An intuitionistic fuzzy data-driven product ranking model using sentiment analysis and multi-criteria decision-making," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    11. Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).
    12. Phillips, Paul & Zigan, Krystin & Santos Silva, Maria Manuela & Schegg, Roland, 2015. "The interactive effects of online reviews on the determinants of Swiss hotel performance: A neural network analysis," Tourism Management, Elsevier, vol. 50(C), pages 130-141.
    Full references (including those not matched with items on IDEAS)

    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. Liu, Fan & Liao, Huchang & Al-Barakati, Abdullah, 2023. "Physician selection based on user-generated content considering interactive criteria and risk preferences of patients," Omega, Elsevier, vol. 115(C).
    2. Ahani, Ali & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh & Sanzogni, Louis & Tarik, A. Rashid & Knox, Kathy & Samad, Sarminah & Ibrahim, Othman, 2019. "Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 331-343.
    3. Shan, Wei & Wang, Jiaxuan & Shi, Xiaoxiao & David Evans, Richard, 2024. "The impact of electronic word-of-mouth on patients’ choices in online health communities: A cross-media perspective," Journal of Business Research, Elsevier, vol. 173(C).
    4. Yinfeng Du & Zhen-Song Chen & Jie Yang & Juan Antonio Morente-Molinera & Lu Zhang & Enrique Herrera-Viedma, 2023. "A Textual Data-Oriented Method for Doctor Selection in Online Health Communities," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    5. Raksmey Sann & Pei-Chun Lai & Hui-Chen Chang, 2020. "Does Culture of Origin Have an Impact on Online Complaining Behaviors? The Perceptions of Asians and Non-Asians," Sustainability, MDPI, vol. 12(5), pages 1-37, February.
    6. Francisco Liébana-Cabanillas & Nidhi Singh & Zoran Kalinic & Elena Carvajal-Trujillo, 2021. "Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: a multi-analytical approach," Information Technology and Management, Springer, vol. 22(2), pages 133-161, June.
    7. Kirillova, Ksenia, 2023. "A review of aesthetics research in tourism:," Annals of Tourism Research, Elsevier, vol. 100(C).
    8. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
    9. Wang, Mingwei & Zhang, Junping & Liang, Decui, 2024. "Multi-period share pledging with sequential three-way proportion decision," Omega, Elsevier, vol. 127(C).
    10. Antonio Marsi & Emanuela Randon, 2021. "Tourist Tax and Ratings of Online Reviews," Working Papers wp1168, Dipartimento Scienze Economiche, Universita' di Bologna.
    11. Zhang, Yishuo & Li, Gang & Muskat, Birgit & Law, Rob & Yang, Yating, 2020. "Group pooling for deep tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 82(C).
    12. Raniah Alsahafi & Ahmed Alzahrani & Rashid Mehmood, 2023. "Smarter Sustainable Tourism: Data-Driven Multi-Perspective Parameter Discovery for Autonomous Design and Operations," Sustainability, MDPI, vol. 15(5), pages 1-64, February.
    13. Boccali, Filippo & Mariani, Marcello M. & Visani, Franco & Mora-Cruz, Alexandra, 2022. "Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    14. Erdogan Koc & Ahu Yazici Ayyildiz, 2021. "Culture’s Influence on the Design and Delivery of the Marketing Mix Elements in Tourism and Hospitality," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
    15. Jessie Bravo & Roger Alarcón & Carlos Valdivia & Oscar Serquén, 2023. "Application of Machine Learning Techniques to Predict Visitors to the Tourist Attractions of the Moche Route in Peru," Sustainability, MDPI, vol. 15(11), pages 1-25, June.
    16. Harman Preet Singh & Mohammad Alshallaqi & Mohammed Altamimi, 2023. "Predicting Critical Factors Impacting Hotel Online Ratings: A Comparison of Religious and Commercial Destinations in Saudi Arabia," Sustainability, MDPI, vol. 15(15), pages 1-25, August.
    17. Adjei Peter Darko & Decui Liang & Yinrunjie Zhang & Agbodah Kobina, 2023. "Service quality in football tourism: an evaluation model based on online reviews and data envelopment analysis with linguistic distribution assessments," Annals of Operations Research, Springer, vol. 325(1), pages 185-218, June.
    18. Liu, Congzheng & Letchford, Adam N. & Svetunkov, Ivan, 2022. "Newsvendor problems: An integrated method for estimation and optimisation," European Journal of Operational Research, Elsevier, vol. 300(2), pages 590-601.
    19. Yanlin Shi & Qingjin Peng, 2023. "Conceptual design of product structures based on WordNet hierarchy and association relation," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2655-2671, August.
    20. Hua, Nan & Yang, Yang, 2017. "Systematic effects of crime on hotel operating performance," Tourism Management, Elsevier, vol. 60(C), pages 257-269.

    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:jomega:v:129:y:2024:i:c:s0305048324001269. 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/wps/find/journaldescription.cws_home/375/description#description .

    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.