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Feeling a destination through the “right” photos: A machine learning model for DMOs’ photo selection

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  • Deng, Ning
  • Li, Xiang (Robert)

Abstract

Photos are important carriers in destination image communication. Currently, efficiently selecting appropriate photos for destination promotion remains a major challenge for DMOs, a problem closely related to the discrepancy between projected and received destination images. During the photo selection process, contents that can best evoke viewers' potential motives should be considered favorably. This project proposes and implements a machine learning-based model to assist DMOs with photo content selection. The proposed protocol ranks candidate photos describing a specific theme from viewers’ perspective. In the present empirical study, over 20,000 Flickr photos of New York City taken by foreign tourists were analyzed to demonstrate the effectiveness of this approach. The results indicate that the proposed method can facilitate the selection of destination photos and address the pronounced gap between projected and received images.

Suggested Citation

  • Deng, Ning & Li, Xiang (Robert), 2018. "Feeling a destination through the “right” photos: A machine learning model for DMOs’ photo selection," Tourism Management, Elsevier, vol. 65(C), pages 267-278.
    • Handle: RePEc:eee:touman:v:65:y:2018:i:c:p:267-278
    DOI: 10.1016/j.tourman.2017.09.010
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    References listed on IDEAS

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    1. Pan, Steve & Lee, Jinsoo & Tsai, Henry, 2014. "Travel photos: Motivations, image dimensions, and affective qualities of places," Tourism Management, Elsevier, vol. 40(C), pages 59-69.
    2. Lo, Iris Sheungting & McKercher, Bob & Lo, Ada & Cheung, Catherine & Law, Rob, 2011. "Tourism and online photography," Tourism Management, Elsevier, vol. 32(4), pages 725-731.
    3. Stepchenkova, Svetlana & Zhan, Fangzi, 2013. "Visual destination images of Peru: Comparative content analysis of DMO and user-generated photography," Tourism Management, Elsevier, vol. 36(C), pages 590-601.
    4. Hunter, William Cannon, 2016. "The social construction of tourism online destination image: A comparative semiotic analysis of the visual representation of Seoul," Tourism Management, Elsevier, vol. 54(C), pages 221-229.
    5. Kim, Hany & Stepchenkova, Svetlana, 2015. "Effect of tourist photographs on attitudes towards destination: Manifest and latent content," Tourism Management, Elsevier, vol. 49(C), pages 29-41.
    6. Anand, Punam & Holbrook, Morris B & Stephens, Debra, 1988. "The Formation of Affective Judgments: The Cognitive-Affective Model versus the Independence Hypothesis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(3), pages 386-391, December.
    7. Amaro, Suzanne & Duarte, Paulo & Henriques, Carla, 2016. "Travelers’ use of social media: A clustering approach," Annals of Tourism Research, Elsevier, vol. 59(C), pages 1-15.
    8. Smith, Wayne W. & Li, Xiang (Robert) & Pan, Bing & Witte, Mark & Doherty, Sean T., 2015. "Tracking destination image across the trip experience with smartphone technology," Tourism Management, Elsevier, vol. 48(C), pages 113-122.
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    Cited by:

    1. Jimenez-Marquez, Jose Luis & Gonzalez-Carrasco, Israel & Lopez-Cuadrado, Jose Luis & Ruiz-Mezcua, Belen, 2019. "Towards a big data framework for analyzing social media content," International Journal of Information Management, Elsevier, vol. 44(C), pages 1-12.
    2. Paül i Agustí, Daniel, 2018. "Characterizing the location of tourist images in cities. Differences in user-generated images (Instagram), official tourist brochures and travel guides," Annals of Tourism Research, Elsevier, vol. 73(C), pages 103-115.

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