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Post-covid China's Tourism Image Projection through Instagram: A Mixed Method Based on Image Tagging

Yuqi Liu
Frontiers in Humanities and Social Sciences, (2025), Vol.5, No.8, pp.265-284
Published: August 20, 2025
DOI: 10.54691/mnrzmj57
PDF: Download Full Text PDF
Abstract

This study addresses the post-pandemic challenges faced by China's tourism industry, particularly focusing on the international image projected through Instagram. Utilizing machine learning-based image tagging techniques combined with Peircean semiotic theory, the study conducts a comprehensive quantitative and qualitative analysis of Instagram photos. The research identifies four key themes in China's tourism imagery: Urban Life, Natural Landscapes, Defense and Technology, and Cultural Activities. The theme of Urban Life highlights the dynamic and resilient nature of Chinese cities, with a particular emphasis on Shanghai. Natural Landscapes showcase China's commitment to ecological conservation and sustainable tourism. Defense and Technology focus on advancements in infrastructure, aerospace, and defense, reflecting national pride and technological prowess. Cultural Activities portray the rich cultural tapestry of China, emphasizing festivals and traditional attire. The findings underscore the critical role of visual content in shaping public perceptions of tourism destinations. By systematically analyzing and interpreting large-scale visual data, this study provides DMOs with valuable insights into effective image projection strategies. This research not only contributes to the theoretical understanding of tourism image construction but also offers practical implications for enhancing the global competitiveness of tourism destinations in the post-pandemic era. The innovative combination of machine learning and semiotic analysis represents a significant advancement in the methodological approaches to tourism image research.

Keywords: Semiotics; image tagging; Instagram; destination-country image; projected image.
APA Citation: Yuqi Liu (2025). Post-covid China's Tourism Image Projection through Instagram: A Mixed Method Based on Image Tagging. Frontiers in Humanities and Social Sciences, 5(8), 265-284. https://doi.org/10.54691/mnrzmj57

References

  1. Hunter, W.C. Semiotic fieldwork on chaordic tourism destination image management in Seoul during COVID-19. Tour. Manag. 2022, 93, 104565. https:// doi.org/ 10.1016 /j. tourman. 2022.104565
  2. State Council of the People's Republic of China. (2021, February 19). China's domestic tourism shrinks in 2020 amid COVID-19 epidemic https:// english.www.gov.cn/ archive/ statistics/ 202102/ 19/content_WS602f6da1c6d0719374af9129.html
  3. State Council of the People's Republic of China. (2022, December 29). China's COVID measures to facilitate cross-border travel, int'l exchanges: spokesperson https:// english.www.gov.cn /archive/statistics/202102/19/content_WS602f6da1c6d0719374af9129.html
  4. State Council of the People's Republic of China. (2023, December 15). China's cultural, tourism sectors see robust recovery, expect higher-quality development https://english. www.gov.cn/ archive/statistics/202102/19/content_WS602f6da1c6d0719374af9129.html
  5. Iordanova, E.; Stainton, H. Cognition, emotion and trust: A comparative analysis of Cambodia’s perceived and projected online image. Tour. Stud. 2019, 19, 496–519. https:// doi.org/ 10.1177/1468797619829152
  6. Zeng, B., & Gerritsen, R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10, 27–36. https://doi.org/10.1016/j.tmp.2014. 01.001
  7. Leung, D., Law, R., Van Hoof, H., & Buhalis, D. (2013). Social media in tourism and hospitality: A literature review. Journal of Travel & Tourism Marketing, 30(1–2), 3–22. https:// doi.org/ 10.1080/10548408.2013.750919
  8. Hung, Y. C., Yang, Y. L., Yang, H. E., & Yahsueh, C. (2011). Factors affecting the adoption of e-commerce for the tourism industry in Taiwan. Asia Pacific Journal of Tourism Research, 16(1), 105–119. https://doi.org/10.1080/10941665.2011.539391
  9. Beyvers, E.M.A.; Herbrich, T. Social media and the European fundamental rights to privacy and data protection. In Proceedings of the 3rd European Conference on Social Media Research EM Normandie, Caen, France, 12–13 June 2016; pp. 33–39.
  10. Zeng, B., & Gerritsen, R. (2014). What do we know about social media in tourism? A review. Tourism Management Perspectives, 10, 27–36. https://doi.org/10.1016/j.tmp.2014. 01.001
  11. Cao, B. (2011). Social media: Definition, history of development, features and future. Journal of Hunan Radio and Television University, 3,65–69.
  12. Song, L., Li, R. Y. M., & Wareewanich, T. (2023). The Cultivation Effect of Architectural Heritage YouTube Videos on Perceived Destination Image. Buildings, 13(2), 508. https:// doi.org/ 10.3390/buildings13020508
  13. 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. https://doi.org/10.1177/1356766717736350
  14. Xiao, X., Fang, C., & Lin, H. (2020). Characterizing tourism destination image using photos’ visual content. ISPRS International Journal of Geo-Information, 9. https://doi.org/10.3390/ijgi9040262
  15. Dong, J. and Li, L. (2022), “Customer visual perception of indoor environments: computer vision analysis of social media photos of cafes in China”, Leisure Sciences, Vol. 9, pp. 1-21.
  16. Li, J., Weng, G., & Pan, Y. (2021). Projected Destination-Country Image in documentaries: Taking wild China and aerial China for example. Journal of Destination Marketing & Management, 20, 100609. https://doi.org/10.1016/j.jdmm.2021.100609
  17. Hunt J D. Image As a Factor in Tourism Development〔D〕. Colorado State University, 1971.
  18. Echtner, C. M., & Ritchie, J. R. B. (1991). The meaning and measurement of destination image. Journal of Tourism Studies, 2(2), 2–12.
  19. Florian Kock, Alexander Josiassen, A. George Assaf, Advancing destination image: The destination content model, Annals of Tourism Research, Volume 61,2016, Pages 28-44, ISSN 0160-7383, https://doi.org/10.1016/j.annals.2016.07.003.
  20. Baloglu, S., & McCleary, K.W. A model of destination image formation. Ann. Tour. Res. 1999, 26, 868–897. https://doi.org/10.1016/S0160-7383(99)00031-1
  21. Lian, T., & Yu, C. (2017). Representation of online image of tourist destination: A content analysis of Huangshan. Asia Pacific Journal of Tourism Research, 22(10), 1063–1082. https:// doi.org/ 10.1080/10941665.2017.1368678
  22. Afshardoost, M., & Eshaghi, M. S. (2020). Destination image and tourist behavioral intentions: A meta-analysis. Tourism Management, 81, Article 104154. https:// doi.org/ 10.1016/ j.tourman. 2020.104154
  23. Zhang, H., Fu, X., Cai, L. A., & Lu, L. (2014). Destination image and tourist loyalty: A meta-analysis. Tourism Management, 40, 213 – 223. https://doi.org/10.1016/j.tourman.2013.06.006
  24. Augustyn, M. (1998). National strategies for rural tourism development and sustainability: The polish experience. Journal of Sustainable Tourism, 6(3), 191–209. https:// doi.org/ 10.1080/ 09669589808667311
  25. Zhang, H., Xu, F., Leung, H. H., & Cai, L. A. (2016). The influence of destination-country image on prospective tourists’ visit intention: Testing three competing models. Asia Pacific Journal of Tourism Research, 21(7), 811–835. https://doi.org/10.1080/10941665.2015.1075566
  26. Campo, S., & Alvarez, M. D. (2010). Country versus destination image in a developing country. Journal of Travel and Tourism Marketing, 27(7), 749–765. https:// doi.org/ 10.1080/ 10548408. 2010.519679
  27. Mossberg, L., & Kleppe, I. A. (2005). Country and destination image – different or similar image concepts? The Service Industries Journal, 25 (4), 493 - 503. https:// doi.org/ 10.1080/ 02642060500092147
  28. Nadeau, J., Heslop, L., O’Reilly, N., & Luk, P. (2008). Destination in a country image context. Annals of Tourism Research, 35(1), 84–106. https://doi.org/10.1016/j.annals.2007.06.012
  29. Dedeoğlu, B. B. (2019). Shaping tourists’ destination quality perception and loyalty through destination country image: The importance of involvement and perceived value. Tourism Management Perspectives, 29, 105–117. https://doi.org/10.1016/j.tmp.2018.11.005
  30. Gartner, W. C. (1993). Image formation process. Journal of Travel Research, 31(4), 10–15. https://doi.org/10.1177/004728759303100402
  31. Ji, S., & Wall, G. (2015). Understanding supply- and demand-side destination image relationships: The case of Qingdao, China. Journal of Vacation Marketing, 21(2), 205–222. https:// doi.org /10.1177/1356766714542189
  32. Beerli, A., & Martin, J. D. (2004). Factors influencing destination images. Annals of Tourism Research, 31, 657–681. https://doi.org/10.1016/j.annals.2004.01.010
  33. Grosspietsch, M. (2006). Perceived and projected images of Rwanda: Visitor and international tour operator perspectives. Tourism Management, 27(2), 225–234. https:// doi.org/ 10.1016/ j.tourman.2004.08.005
  34. Pappu, R.; Quester, P. Country equity: Conceptualization and empirical evidence. Int. Bus. Rev. 2010, 19, 276–291. https://doi.org/10.1016/j.ibusrev.2009.12.006
  35. Bordelon, L.A., & Ferreira, S.L.A. (2017). Tourist photographs and destination imagery on social media: Reading the Stellenbosch Winelands through a tourist lens. Tourism Review International, 21(3), 317-329. https://doi.org/10.3727/154427217x15022104437765
  36. Koltringer, C.; Dickinger, A. Analyzing Destination Branding and Image from Online Sources: A Web Content Mining Approach. J. Bus. Res. 2015, 68, 1836–1843. https:// doi.org/ 10.1016 /j.jbusres.2015.01.011
  37. Mak, A.H.N. Online destination image: Comparing national tourism organization’s and tourists’ perspectives. Tour. Manag. 2017, 60, 280–297. https://doi.org/10.1016/j.tourman.2016.12.012
  38. Mirzaalian, F., & Halpenny, E. (2021). Exploring destination loyalty: Application of social media analytics in a nature-based tourism setting. Journal of Destination Marketing & Management, 20, 100598. https://doi.org/10.1016/j.jdmm.2021.100598
  39. Zhao, Z., Zhu, M., & Hao, X. (2018). Share the Gaze: Representation of destination image on the Chinese social platform WeChat Moments. Journal of Travel and Tourism Marketing, 35(6):726-739. https://doi.org/10.1080/10548408.2018.1432449
  40. Mull, I. R., & Lee, S. E. (2014). “PIN” pointing the motivational dimensions behind Pinterest. Computers in Human Behavior, 33, 192-200. https://doi.org/10.1016/j.chb.2014.01.011
  41. Herath, H. M. H. M., & Stanford, D. (2017). The analysis of responsible tourism photography and its influence on destination image in Sri Lanka. In Proceedings of International Conference on Hospitality and Tourism Management, Colombo, Sri Lanka, pp. 27. https:// tourismconference.co /wp-content/uploads/2018/03/Book_Abstracts_ICOHT_ 2017.pdf
  42. Park, E., & Kim, S. (2018). Are we doing enough for visual research in tourism? The past, present, and future of tourism studies using photographic images. International Journal of Tourism Research, 20(4), 433–441. https://doi.org/10.1002/jtr.2194
  43. 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. https://doi.org/10.1016/j.tourman.2015.11.012
  44. Arefieva, V., Egger, R., & Yu, J. (2021). A machine learning approach to cluster destination image on Instagram. Tourism Management, 85, 104318. https://doi.org/10.1016/j.tourman.2021.104318
  45. Zhang, K., Zhang, J., Shang, X., Yang, J., & Li, C. (2023). Linking UGP’ s affective and cognitive concepts together for tourism destination image development. Current Issues in Tourism, 1–16. https://doi.org/10.1080/13683500.2023.2288161
  46. Nanne, A. J., Antheunis, M. L., Van Der Lee, C. G., Postma, E. O., Wubben, S., & Van Noort, G. (2020). The Use of Computer Vision to Analyze Brand-Related User Generated Image Content. Journal of Interactive Marketing, 50(1), 156–167. https://doi.org/10.1016/j.intmar.2019.09.003
  47. Bell, E., & Davison, J. (2013). Visual management studies: Empirical and theoretical approaches. International Journal of Management Reviews, 15(2), 167–184. https://doi.org/10.1111/j.1468-2370.2012.00342.x
  48. Barthes, R. (1967). Elements of Semiology.
  49. ZHAO Yi-heng. Cultural Semiotics Studies: Present Situation and Future Trends. Journal of Southwest University for Nationalities (Humanities and Social Science), 2009, 30(12): 169-172.
  50. Shumaker, S.A., & Taylor, R.B. (1983). Toward a Clarification of People-Place Relationships: A Model of Attachment to Place [J]. Environmental psychology.
  51. Rose, G. (2012). Visual methodologies: An introduction to researching with visual materials. Thousand Oaks, CA: Sage Publication.
  52. Rodriguez L and Dimitrova D (2011) The levels of visual framing. Journal of Visual Literacy 30 (1): 48–65. https://doi.org/10.1080/23796529.2011.11674684
  53. Echtner, C. M. (1999) ‘The Semiotic Paradigm: Implications for Tourism Research’, Tourism Management 20: 47–57. https://doi.org/10.1016/S0261-5177(98)00093-2
  54. MacCannell, D. (1976). The tourist: A new theory of the leisure class. Berkeley: University of California Press.
  55. Zhang, X., & Sheng, J. (2017). A Peircean semiotic interpretation of a social sign. Annals of Tourism Research, 64, 163–173. https://doi.org/10.1016/j.annals.2017.04.002
  56. Pennington, W. J., & Thomsen, C. R. (2010). A semiotic model of destination representations applied to cultural and heritage tourism marketing. Scandinavian Journal of Hospitality and Tourism, 10(1), 33–53. https://doi.org/10.1080/ 15022250903561895
  57. Mele, E., Filieri, R., & De Carlo, M. (2023). Pictures of a crisis. Destination marketing organizations’ Instagram communication before and during a global health crisis. Journal of Business Research, 163, 113931. https://doi.org/10.1016/j.jbusres.2023.113931
  58. Weber, R. P. (1990). Basic content analysis. Beverly Hills, CA: Sage.
  59. Krippendorff, B. K. (2010). Content analysis: An introduction to its methodology. Thousand Oaks, CA: Sage Publications.
  60. Hosseini, H., Xiao, B., & Poovendran, R. (2017). Google’s cloud vision API is not robust to noise. Paper presented at the 2017 16th IEEE international conference on machine learning and applications (ICMLA). https://doi.org/10.1109/ICMLA.2017.0-126
  61. Jing, P., Cai, Y., Wang, B., Wang, B., Huang, J., Jiang, C., & Yang, C. (2023). Listen to social media users: Mining Chinese public perception of automated vehicles after crashes. Transportation Research Part F: Traffic Psychology and Behaviour, 93, 248–265. https://doi.org/10.1016/j.trf.2023.01.018
  62. Ghosh DD, Guha R. What are we 'tweeting' about obesity? Mapping tweets with Topic Modeling and Geographic Information System. Cartogr Geogr Inf Sci. 2013;40(2):90-102. Doi: 10.1080/ 15230406. 2013.776210. PMID: 25126022; PMCID: PMC4128420.
  63. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent dirichlet allocation. J. Mach. Learn. Res. 3, null (3/1/2003), 993–1022.
  64. Guo, Y., Barnes, S. J., & Jia, Q. (2017). Mining meaning from online ratings and reviews: Tourist satisfaction analysis using Latent Dirichlet allocation. Tourism Management, 59, 467–483. https://doi.org/10.1016/j.tourman.2016.09.009
  65. Pavlinek, M., & Podgorelec, V. (2017). Text classification method based on self-training and LDA topic models. Expert Systems with Applications , 80 ,83 – 93. https:// doi.org/ 10.1016 /j.eswa.2017.03.008
  66. Stevens, K.; Kegelmeyer, P.; Andrzejewski, D.; Buttler, D. Exploring topic coherence over many models and many topics. In Proceedings of the Empirical Methods in Natural Language Processing 2012, Jeju Island, Korea, 12–14 July 2012.
  67. Aman, J. J. C., Smith-Colin, J., & Zhang, W. (2021). Listen to E-Scooter Riders: Mining Rider Satisfaction Factors from App Store Reviews. Transportation Research Part D: Transport and Environment, 95(June), 102856. https://doi.org/10.1016/j.trd.2021.102856
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