IDEAS home Printed from https://ideas.repec.org/a/spr/infott/v16y2016i1d10.1007_s40558-015-0035-y.html
   My bibliography  Save this article

Analyzing user reviews in tourism with topic models

Author

Listed:
  • Marco Rossetti

    (University of Milano-Bicocca)

  • Fabio Stella

    (University of Milano-Bicocca)

  • Markus Zanker

    (Alpen-Adria-Universität Klagenfurt)

Abstract

User generated content in general and textual reviews in particular constitute a vast source of information for the decision making of tourists and management and are therefore a key component for e-tourism. This paper provides a description of the topic model method with a particular application focus on the tourism domain. It therefore contributes different application scenarios where the topic model method processes textual reviews in order to provide decision support and recommendations to online tourists as well as to build a basis for further analytics. In the latter case the delivery of additional semantics helps digging into the enormous amounts of data that are continuously collected in present time. The contribution therefore consists of new models based on the topic model method and results from experimenting with user generated review data on restaurants and hotels.

Suggested Citation

  • Marco Rossetti & Fabio Stella & Markus Zanker, 2016. "Analyzing user reviews in tourism with topic models," Information Technology & Tourism, Springer, vol. 16(1), pages 5-21, March.
    • Handle: RePEc:spr:infott:v:16:y:2016:i:1:d:10.1007_s40558-015-0035-y
    DOI: 10.1007/s40558-015-0035-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40558-015-0035-y
    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/s40558-015-0035-y?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. Scott Deerwester & Susan T. Dumais & George W. Furnas & Thomas K. Landauer & Richard Harshman, 1990. "Indexing by latent semantic analysis," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 41(6), pages 391-407, September.
    2. Xiang, Zheng & Gretzel, Ulrike, 2010. "Role of social media in online travel information search," Tourism Management, Elsevier, vol. 31(2), pages 179-188.
    3. Zehrer, Anita & Crotts, John C. & Magnini, Vincent P., 2011. "The perceived usefulness of blog postings: An extension of the expectancy-disconfirmation paradigm," Tourism Management, Elsevier, vol. 32(1), pages 106-113.
    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. Julia Neidhardt & Nataliia Rümmele & Hannes Werthner, 0. "Predicting happiness: user interactions and sentiment analysis in an online travel forum," Information Technology & Tourism, Springer, vol. 0, pages 1-19.
    2. Georgia Yfantidou & Sofia Yfantidou & Dimitra Karanatsiou & Angelos Liontakis & Mairi Maniopoulou & Panagiota Balaska & Alkistis Papaioannou & Vassiliki Vassilopoulou, 2024. "Experience Economy Perspective on Recreational Fishing Tourism Travelers’ Reviews: A Data Science Approach," Tourism and Hospitality, MDPI, vol. 5(2), pages 1-27, April.
    3. Alireza Alaei & Ying Wang & Vinh Bui & Bela Stantic, 2023. "Target-Oriented Data Annotation for Emotion and Sentiment Analysis in Tourism Related Social Media Data," Future Internet, MDPI, vol. 15(4), pages 1-21, April.
    4. Choi, Hyunhong & Woo, JongRoul, 2022. "Investigating emerging hydrogen technology topics and comparing national level technological focus: Patent analysis using a structural topic model," Applied Energy, Elsevier, vol. 313(C).
    5. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2017. "‘You will like it!’ using open data to predict tourists' response to a tourist attraction," Tourism Management, Elsevier, vol. 60(C), pages 430-438.
    6. Antonio Moreno-Ortiz & Soluna Salles-Bernal & Aroa Orrequia-Barea, 2019. "Design and validation of annotation schemas for aspect-based sentiment analysis in the tourism sector," Information Technology & Tourism, Springer, vol. 21(4), pages 535-557, December.
    7. Julia Neidhardt & Nataliia Rümmele & Hannes Werthner, 2017. "Predicting happiness: user interactions and sentiment analysis in an online travel forum," Information Technology & Tourism, Springer, vol. 17(1), pages 101-119, March.
    8. Michela Fazzolari & Marinella Petrocchi, 2018. "A study on online travel reviews through intelligent data analysis," Information Technology & Tourism, Springer, vol. 20(1), pages 37-58, 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. Bronner, Fred & de Hoog, Robert, 2016. "Travel websites: Changing visits, evaluations and posts," Annals of Tourism Research, Elsevier, vol. 57(C), pages 94-112.
    2. Xiang, Zheng & Magnini, Vincent P. & Fesenmaier, Daniel R., 2015. "Information technology and consumer behavior in travel and tourism: Insights from travel planning using the internet," Journal of Retailing and Consumer Services, Elsevier, vol. 22(C), pages 244-249.
    3. Irina Wedel & Michael Palk & Stefan Voß, 2022. "A Bilingual Comparison of Sentiment and Topics for a Product Event on Twitter," Information Systems Frontiers, Springer, vol. 24(5), pages 1635-1646, October.
    4. Mahan, Joseph E. & Seo, Won Jae & Jordan, Jeremy S. & Funk, Daniel, 2015. "Exploring the impact of social networking sites on running involvement, running behavior, and social life satisfaction," Sport Management Review, Elsevier, vol. 18(2), pages 182-192.
    5. Tao Liu & Ying Zhang & Huan Zhang & Xiping Yang, 2021. "A Methodological Workflow for Deriving the Association of Tourist Destinations Based on Online Travel Reviews: A Case Study of Yunnan Province, China," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    6. Ahmed Ibrahim Alzahrani & T. Ramayah & Nalini Suppiah & Osama Alfarraj & Nasser Alalwan, 2020. "Modeling Blog Usage From a Developing Country Perspective Using Structural Equation Modeling (SEM)," SAGE Open, , vol. 10(3), pages 21582440209, July.
    7. Mohammed Salem Binwahlan, 2023. "Polynomial Networks Model for Arabic Text Summarization," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 10(2), pages 74-84, February.
    8. Curci, Ylenia & Mongeau Ospina, Christian A., 2016. "Investigating biofuels through network analysis," Energy Policy, Elsevier, vol. 97(C), pages 60-72.
    9. 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).
    10. Chao Wei & Senlin Luo & Xincheng Ma & Hao Ren & Ji Zhang & Limin Pan, 2016. "Locally Embedding Autoencoders: A Semi-Supervised Manifold Learning Approach of Document Representation," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-20, January.
    11. Yanlong Guo & Jiaying Yu & Han Zhang & Zuoqing Jiang, 2022. "A Study on Cultural Context Perception in Huizhou Cultural and Ecological Reserve Based on Multi-Criteria Decision Analysis," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    12. Krakover, Shaul & Corsale, Andrea, 2021. "Sieving tourism destinations: Decision-making processes and destination choice implications," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7(1), pages 33-43.
    13. Qu, Hailin & Lee, Haeyoung, 2011. "Travelers’ social identification and membership behaviors in online travel community," Tourism Management, Elsevier, vol. 32(6), pages 1262-1270.
    14. Li, Xiangping & Li, Xiang (Robert) & Hudson, Simon, 2013. "The application of generational theory to tourism consumer behavior: An American perspective," Tourism Management, Elsevier, vol. 37(C), pages 147-164.
    15. Benjamin Appiah Osei & Ama Nyenkua Abenyin, 2016. "Applying the Engell–Kollat–Blackwell model in understanding international tourists’ use of social media for travel decision to Ghana," Information Technology & Tourism, Springer, vol. 16(3), pages 265-284, September.
    16. Antoniadis, Konstantinos & Grougiou, Vasiliki & Zafiropoulos, Kostas & Vrana, Vasiliki & Theocharidis, Anastasios Ioannis, 2018. "The use of Facebook and Twitter by DMOs in Europe," MPRA Paper 98936, University Library of Munich, Germany.
    17. Maksym Polyakov & Morteza Chalak & Md. Sayed Iftekhar & Ram Pandit & Sorada Tapsuwan & Fan Zhang & Chunbo Ma, 2018. "Authorship, Collaboration, Topics, and Research Gaps in Environmental and Resource Economics 1991–2015," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 217-239, September.
    18. Ding, Ying, 2011. "Community detection: Topological vs. topical," Journal of Informetrics, Elsevier, vol. 5(4), pages 498-514.
    19. Klaus Gugler & Florian Szücs & Ulrich Wohak, 2023. "Start-up Acquisitions, Venture Capital and Innovation: A Comparative Study of Google, Apple, Facebook, Amazon and Microsoft," Department of Economics Working Papers wuwp340, Vienna University of Economics and Business, Department of Economics.
    20. Juan Shi & Kin Keung Lai & Ping Hu & Gang Chen, 2018. "Factors dominating individual information disseminating behavior on social networking sites," Information Technology and Management, Springer, vol. 19(2), pages 121-139, June.

    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:infott:v:16:y:2016:i:1:d:10.1007_s40558-015-0035-y. 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.