IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-031-54338-8_19.html
   My bibliography  Save this book chapter

Analysis of Facial Expression in Videos Promoting Tourist Destinations

In: Recent Advancements in Tourism Business, Technology and Social Sciences

Author

Listed:
  • Fernando Toro Sánchez

    (University of Seville)

Abstract

With the evolution of web technology, users provide us with an enormous amount of voluntary and involuntary data that can generate extraordinarily rich information for the promotion of tourism products, which is why the importance of this work lies in exploring, analysing and organising the feelings provoked after viewing a promotional video. This work is based on sentiment analysis (SA) and, in particular, on the analysis of the facial experience within SA, which is based on a series of technologies framed in neuromarketing that are experiencing great growth given the importance of information supported by audiovisual media, in particular video. This work presents a study on the feelings found in the exhibition of promotional videos of a certain tourist destination, finding interesting conclusions based on the identification of different emotional valences such as: fear, anger, joy, sadness, contempt, disgust and surprise, the same ones described by the psychologist Paul Ekman. For this purpose, algorithmic facial recognition techniques based on positional vectors are used. The results obtained reveal the importance of content in tourism promotion and, in particular, resolve and facilitate methodologies to generate demographically segmented and effective content for each target tourist audience.

Suggested Citation

  • Fernando Toro Sánchez, 2024. "Analysis of Facial Expression in Videos Promoting Tourist Destinations," Springer Proceedings in Business and Economics, in: Vicky Katsoni & George Cassar (ed.), Recent Advancements in Tourism Business, Technology and Social Sciences, pages 347-358, Springer.
  • Handle: RePEc:spr:prbchp:978-3-031-54338-8_19
    DOI: 10.1007/978-3-031-54338-8_19
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    Emotion recognition; Machine learning; Facial expression analysis; Sentiment analysis; Tourist destination;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    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:prbchp:978-3-031-54338-8_19. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.