IDEAS home Printed from https://ideas.repec.org/a/spr/infott/vyid10.1007_s40558-017-0079-2.html
   My bibliography  Save this article

Predicting happiness: user interactions and sentiment analysis in an online travel forum

Author

Listed:
  • Julia Neidhardt

    (TU Wien)

  • Nataliia Rümmele

    (TU Wien)

  • Hannes Werthner

    (TU Wien)

Abstract

Web sources of tourism services provide valuable resources of knowledge not only for the travellers but also for the companies. Tourism operators are increasingly aware that user related data should be regarded as an important asset. Furthermore, as data is permanently generated and always available, the landscape of empirical research is changing. In this paper, user activities and interactions in the tourism domain are analysed. In particular, the emotions of the users regarding their forthcoming trips are studied with the objective to characterize interdependencies between them. Social network analysis is applied to examine interactions between the users. To capture their emotions, text mining techniques and sentiment analysis are applied to construct a measure, which is based on free-text comments in a travel forum. The experimental outcome provides some evidence that the network has an effect on the sentiment of the users.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:infott:v::y::i::d:10.1007_s40558-017-0079-2
    DOI: 10.1007/s40558-017-0079-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40558-017-0079-2
    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/s40558-017-0079-2?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. 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.
    2. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    3. Mike Thelwall & David Wilkinson & Sukhvinder Uppal, 2010. "Data mining emotion in social network communication: Gender differences in MySpace," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(1), pages 190-199, January.
    4. M. Mitrović & G. Paltoglou & B. Tadić, 2010. "Networks and emotion-driven user communities at popular blogs," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 597-609, October.
    5. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, September.
    6. Költringer, Clemens & Dickinger, Astrid, 2015. "Analyzing destination branding and image from online sources: A web content mining approach," Journal of Business Research, Elsevier, vol. 68(9), pages 1836-1843.
    7. Sergej Schmunk & Wolfram Höpken & Matthias Fuchs & Maria Lexhagen, 2013. "Sentiment Analysis: Extracting Decision-Relevant Knowledge from UGC," Springer Books, in: Zheng Xiang & Iis Tussyadiah (ed.), Information and Communication Technologies in Tourism 2014, edition 127, pages 253-265, Springer.
    8. Mike Thelwall & David Wilkinson & Sukhvinder Uppal, 2010. "Data mining emotion in social network communication: Gender differences in MySpace," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(1), pages 190-199, January.
    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. 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.
    2. Chmiel, Anna & Sobkowicz, Pawel & Sienkiewicz, Julian & Paltoglou, Georgios & Buckley, Kevan & Thelwall, Mike & Hołyst, Janusz A., 2011. "Negative emotions boost user activity at BBC forum," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2936-2944.
    3. Tian Tian & Stijn Speelman, 2021. "Pursuing Development behind Heterogeneous Ideologies: Review of Six Evolving Themes and Narratives of Rural Planning in China," Sustainability, MDPI, vol. 13(17), pages 1-16, September.
    4. Jacqueline Ng Lane & Bruce Ankenman & Seyed Iravani, 2018. "Insight into Gender Differences in Higher Education: Evidence from Peer Reviews in an Introductory STEM Course," Service Science, INFORMS, vol. 10(4), pages 442-456, December.
    5. Setten, Eric & Chen, Steven, 2024. "Playing with emotions: Text analysis of emotional tones in gender-casted Children’s media," Journal of Business Research, Elsevier, vol. 175(C).
    6. Yulei Gavin Zhang & Mandy Yan Dang & Hsinchun Chen, 2020. "An Explorative Study on the Virtual World: Investigating the Avatar Gender and Avatar Age Differences in their Social Interactions for Help-Seeking," Information Systems Frontiers, Springer, vol. 22(4), pages 911-925, August.
    7. Liwen Vaughan, 2016. "Uncovering information from social media hyperlinks: An investigation of twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1105-1120, May.
    8. Avi Rosenfeld & Sigal Sina & David Sarne & Or Avidov & Sarit Kraus, 2018. "WhatsApp usage patterns and prediction of demographic characteristics without access to message content," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(22), pages 647-670.
    9. F. Schweitzer & D. Garcia, 2010. "An agent-based model of collective emotions in online communities," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 77(4), pages 533-545, October.
    10. Chen, Aihui & Lu, Yaobin & Wang, Bin & Zhao, Ling & Li, Ming, 2013. "What drives content creation behavior on SNSs? A commitment perspective," Journal of Business Research, Elsevier, vol. 66(12), pages 2529-2535.
    11. Li, Xianghua & Wang, Zhen & Gao, Chao & Shi, Lei, 2017. "Reasoning human emotional responses from large-scale social and public media," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 182-193.
    12. Anupriya Khan & Satish Krishnan & Jithesh Arayankalam, 2022. "The Role of ICT Laws and National Culture in Determining ICT Diffusion and Well-Being: A Cross-Country Examination," Information Systems Frontiers, Springer, vol. 24(2), pages 415-440, April.
    13. Ibtesam AbdulAziz Bajri & Nada Abdulmajeed Lashkar, 2020. "Saudi Gender Emotional Expressions in Using Instagram," English Language Teaching, Canadian Center of Science and Education, vol. 13(5), pages 1-94, May.
    14. Roser Beneito-Montagut, 2017. "Emotions, Everyday Life, and the Social Web: Age, Gender, and Social Web Engagement Effects on Online Emotional Expression," Sociological Research Online, , vol. 22(4), pages 87-104, December.
    15. Blazquez-Soriano, Amparo & Ramos-Sandoval, Rosmery, 2022. "Information transfer as a tool to improve the resilience of farmers against the effects of climate change: The case of the Peruvian National Agrarian Innovation System," Agricultural Systems, Elsevier, vol. 200(C).
    16. 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.
    17. Martin L. Weitzman, 2015. "A Voting Architecture for the Governance of Free-Driver Externalities, with Application to Geoengineering," Scandinavian Journal of Economics, Wiley Blackwell, vol. 117(4), pages 1049-1068, October.
    18. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    19. Guo Weilong & Minca Andreea & Wang Li, 2016. "The topology of overlapping portfolio networks," Statistics & Risk Modeling, De Gruyter, vol. 33(3-4), pages 139-155, December.
    20. Thomas J. Sargent & John Stachurski, 2022. "Economic Networks: Theory and Computation," Papers 2203.11972, arXiv.org, revised Jul 2022.

    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::y::i::d:10.1007_s40558-017-0079-2. 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.