Computer supported analysis of Thailand’s imagery on Pinterest

References

• Bauer, M. W., & Aarts, B. (2000). Constructing a research corpus. In M. W. Bauer & G. Gaskell (Eds.), Qualitative researching with text, image and sound: A practical handbook for social research (pp. 19–37). London: Sage.
   Google Scholar
• Bell, P. (2001). Content analysis of visual images. In T. Van Leeuwen & C. Jewitt (Eds.), The handbook of visual analysis (pp. 10–34). Thousand Oaks, CA: Sage.
   Google Scholar
• Camprubí, R., Guia, J., & Comas, J. (2013). The new role of tourists in destination image formation. Current Issues in Tourism, 16(2), 203–209. doi: 10.1080/13683500.2012.733358
   Web of Science ®Google Scholar
• Chen, S. H., & Chen, Y. H. (2017). A content-based image retrieval method based on the Google cloud vision API and WordNet. In Asian conference on intelligent information and database systems (pp. 651–662). Cham: Springer.
   Google Scholar
• Deng, N., & Li, X. R. (2018). Feeling a destination through the ‘right’ photos: A machine learning model for DMOs’ photo selection. Tourism Management, 65, 267–278. doi: 10.1016/j.tourman.2017.09.010
   Web of Science ®Google Scholar
• Dodge, S., & Karam, L. (2017). A study and comparison of human and deep learning recognition performance under visual distortions. In 26th international conference on computer communication and networks (ICCCN) (pp. 1–7). Vancouver, Canada.
   Google Scholar
• Garay Tamajón, L., & Cànoves Valiente, G. (2017). Barcelona seen through the eyes of TripAdvisor: Actors, typologies and components of destination image in social media platforms. Current Issues in Tourism, 20(1), 33–37. doi: 10.1080/13683500.2015.1073229
   Web of Science ®Google Scholar
• Gartner, W. C. (1994). Image formation process. Journal of Travel & Tourism Marketing, 2(2-3), 191–216. doi: 10.1300/J073v02n02_12
   Google Scholar
• Ghazali, R. M., & Cai, L. (2014). Social media sites in destination image formation. In A. M. Munar, S. Gyimothy, & L. Cai (Eds.), Tourism social media: Transformations in identity, community and culture (pp. 73–86). Bradford: Emerald Group.
   Google Scholar
• Gleeson, K. (2012). Polytextual thematic analysis for visual data. In P. Reavey (Ed.), Visual methods in psychology: Using and interpreting images in qualitative research (pp. 314–329). New York, NY: Psychology Press.
   Google Scholar
• Govers, R., & Go, F. M. (2004). Projected destination image online: Website content analysis of pictures and text. Information Technology & Tourism, 7(2), 73–89. doi: 10.3727/1098305054517327
   Google Scholar
• Gunn, C. A. (1972). Vacationscape: Designing tourist regions. Austin, Texas: University of Texas.
   Google Scholar
• Haenssle, H. A., Fink, C., Schneiderbauer, R., Toberer, F., Buhl, T., Blum, A., … Uhlmann, L. (2018). Man against machine: Diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists. Annals of Oncology, 29(8), 1836–1842. doi: 10.1093/annonc/mdy166
   PubMed Web of Science ®Google Scholar
• Henkel, R., Henkel, P., Agrusa, W., Agrusa, J., & Tanner, J. (2006). Thailand as a tourist destination: Perceptions of international visitors and Thai residents. Asia Pacific Journal of Tourism Research, 11(3), 269–287. doi: 10.1080/10941660600753299
   Google Scholar
• Herring, S. C. (2010). Web content analysis: Expanding the paradigm. In J. Hunsinger, L. Klastrup, & M. Allen (Eds.), International handbook of internet research (pp. 233–249). Dordrecht: Springer.
   Google Scholar
• Hunter, W. C. (2016). The social construction of tourism online destination image: A comparative semiotic analysis of the visual representation of Seoul. Tourism Management, 54, 221–229. doi: 10.1016/j.tourman.2015.11.012
   Web of Science ®Google Scholar
• Krishnamurthy, S., & Dou, W. (2008). Advertising with user-generated content: A framework and research agenda. Journal of Interactive Advertising, 8(2), 1–4. doi: 10.1080/15252019.2008.10722137
   Google Scholar
• Kwak, H., & An, J. (eds.) (2016). Revealing the hidden patterns of news photos: Analysis of millions of news photos through GDELT and deep learning-based vision apis. Procedings of the tenth international AAAI conference on web and social media. Cologne: AI Access Foundation.
   Google Scholar
• Lomborg, S., & Bechmann, A. (2014). Using APIs for data collection on social media. The Information Society, 30(4), 256–265. doi: 10.1080/01972243.2014.915276
   Web of Science ®Google Scholar
• Lu, W., & Stepchenkova, S. (2015). User-generated content as a research mode in tourism and hospitality applications: Topics, methods, and software. Journal of Hospitality Marketing & Management, 24(2), 119–154. doi: 10.1080/19368623.2014.907758
   Web of Science ®Google Scholar
• Mak, A. H. N. (2017). Online destination image: Comparing national tourism organisation’s and tourists’ perspectives. Tourism Management, 60, 280–297. doi: 10.1016/j.tourman.2016.12.012
   Web of Science ®Google Scholar
• Michaelidou, N., Siamagka, N. T., Moraes, C., & Micevski, M. (2013). Do marketers use visual representations of destinations that tourists value? Comparing visitors’. Image of a destination with marketer-controlled images online. Journal of Travel Research, 52(6), 789–804. doi: 10.1177/0047287513481272
   Web of Science ®Google Scholar
• Michelson, K., & Alvarez Valencia, J. A. (2016). Study abroad: Tourism or education? A multimodal social semiotic analysis of institutional discourses of a promotional website. Discourse & Communication, 10(3), 235–256. doi: 10.1177/1750481315623893
   Web of Science ®Google Scholar
• Minazzi, R. (2015). Social media marketing in tourism and hospitality. New York, NY: Springer.
   Google Scholar
• Munar, A. M. (2010). Technological mediation and user created content in tourism. CIBEM Working Paper Series, Copenhagen Business School. Retrieved from https://openarchive.cbs.dk/bitstream/handle/10398/8034/workingpaper1_amm_socialmedia_april10.pdf?sequence=1
   Google Scholar
• Munar, A. M. (2011). Tourist-created content: Rethinking destination branding. International Journal of Culture, Tourism and Hospitality Research, 5(3), 291–305. doi: 10.1108/17506181111156989
   Google Scholar
• Munar, A. M., & Jacobsen, J. K. S. (2014). Motivations for sharing tourism experiences through social media. Tourism Management, 43, 46–54. doi: 10.1016/j.tourman.2014.01.012
   Web of Science ®Google Scholar
• Pan, B, Litvin, S. W, & Goldman, H. (2006). Real users, real trips, and real queries: An analysis of destination search on a search engine. In Annual Conference of Travel and Tourism Research Association (TTRA) (pp. 16–18). Ireland, Dublin.
   Google Scholar
• Phillips, B. J., Miller, J., & McQuarrie, E. F. (2014). Dreaming out loud on Pinterest: New forms of indirect persuasion. International Journal of Advertising, 33(4), 633–655. doi: 10.2501/IJA-33-4-633-655
   Web of Science ®Google Scholar
• Picazo, P., & Moreno-Gil, S. (2019). Analysis of the projected image of tourism destinations on photographs: A literature review to prepare for the future. Journal of Vacation Marketing, 25(1), 3–24. doi: 10.1177/1356766717736350
   Web of Science ®Google Scholar
• Pinterest audience demographics. (2018). Retrieved from https://business.pinterest.com/en/audience-demographics-user-stats
   Google Scholar
• Rittichainuwat, B. N., Qu, H., & Brown, T. J. (2001). Thailand’s international travel image: Mostly favorable. The Cornell Hotel and Restaurant Administration Quarterly, 42(2), 82–95.
   Google Scholar
• Robinson, S. (2017). Exploring the cloud vision API. Retrieved from https://medium.com/@srobtweets/exploring-the-cloud-vision-api-1af9bcf080b8
   Google Scholar
• Rose, G. (2012). Visual methodologies: An introduction to researching with visual material. London: Sage.
   Google Scholar
• Rowett, P. (2015, August 7.). How pinterest can drive visitation & sales for the tourism industry. Retrieved from https://tourismeschool.com/blog/can-pinterest-really-drive-visitation-sales-for-the-tourism-industry/#sthash.HljI9274.dpuf
   Google Scholar
• Silverman, D. (2009). Doing qualitative research: A practical handbook (3rd ed.). London: Sage.
   Google Scholar
• Song, S. G., & Kim, D. Y. (2016). A pictorial analysis of destination images on pinterest: The case of Tokyo, Kyoto, and Osaka, Japan. Journal of Travel & Tourism Marketing, 33(5), 687–701. doi: 10.1080/10548408.2016.1167384
   Web of Science ®Google Scholar
• Stepchenkova, S., & Zhan, F. (2013). Visual destination images of Peru: Comparative content analysis of DMO and user-generated photography. Tourism Management, 36, 590–601. doi: 10.1016/j.tourman.2012.08.006
   Web of Science ®Google Scholar
• Tapachai, N., & Waryszak, R. (2000). An examination of the role of beneficial image in tourist destination selection. Journal of Travel Research, 39(1), 37–44. doi: 10.1177/004728750003900105
   Google Scholar
• Tsang, S. H. (2018). Review: Inception-v3  –  1st runner up. Retrieved from https://medium.com/@sh.tsang/review-inception-v3-1st-runner-up-image-classification-in-ilsvrc-2015-17915421f77c
   Google Scholar