Sentiment Analysis of Chinese Tourists to Marine Tourism Resource in Sabah
Abstract
With the tourism industry's recovery, there is an increased demand for outbound Chinese tourists. With Chinese tourists as an important submarket in Sabah, a better understanding of Chinese tourists' perceptions of destination tourism is crucial for development. In this study, the representative Tanjung Aru Beach in Sabah was selected as the study case, and the review content was selected through the travellers’ reviews on China's largest travel online platform - Ctrip.com, as the study sample. Through Octopus Collector 8, the text data was analyzed for word frequency, web semantics, and sentiment using the ROST CM6 tool. The results of the study found that most of the Chinese tourists at Tanjung Aru Beach gave satisfactory comments. These positive comments focused mainly on the natural landscape and resources of the beach, the services of the Shangri-La Hotel, the ease of language communication, and the local cuisine. More often than not, Chinese tourists mentioned the beach's sunsets, evening sunsets, flaming clouds, sand, cloud formations, and sea breezes. The study also found that “beach” and “sunset” were the resources that Chinese tourists recognized for the attraction, with the majority of reviews revolving around these two themes. It should be noted that Chinese tourists showed dissatisfaction with the sanitary environment and facilities at Tanjung Aru Beach. The study concludes with recommendations for management.
Downloads
References
Chen, F., Lai, M., & Huang, H. (2020). Can marine parks become ecotourism destinations? Evidence from stakeholders' perceptions of suitability. Ocean & Coastal Management, 196, 105307. https://doi.org/10.1016/j.ocecoaman.2020.105307
China Internet Network Information Center. (2023). China Internet development report. Retrieved from https://baijiahao.baidu.com/s?id=1794250384458690555&wfr=spider&for=pc
China Tourism Association. (2024). Tourism statistics. Retrieved from http://www.ctaweb.org/html/lysjzx/index.html
Dholakia, R. R., & Zhao, M. (2010). Effects of online store attributes on customer satisfaction and repurchase intentions. International Journal of Retail and Distribution Management, 38(7), 482-496. https://doi.org/10.1108/09590551011052098
Dimitrovski, D., Lemmetyinen, A., Nieminen, L., & Pohjola, T. (2021). Understanding coastal and marine tourism sustainability: A multi-stakeholder analysis. Journal of Destination Marketing & Management, 19, 100554. https://doi.org/10.1016/j.jdmm.2021.100554
Flores-Ruiz, D., Elizondo-Salto, A., & Barroso-González, M. D. L. O. (2021). Using social media in tourist sentiment analysis: A case study of Andalusia during the COVID-19 pandemic. Sustainability, 13(7), 3836. https://doi.org/10.3390/su13073836
Frias-Martinez, V., Soto, V., Hohwald, H., & Frias-Martinez, E. (2012, September). Characterizing urban landscapes using geolocated tweets. In 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Conference on Social Computing (pp. 239-248). IEEE. https://doi.org/10.1109/PASSAT/SocialCom.2012.112
Guo, X., Hu, L., Li, M., & Wang, Y. (2024). Construction of a tourist sentiment analysis model from the perspective of online review data mining: A case study of Zhaoqing Qixingyan Scenic Area. Science and Technology Innovation and Application, 13, 9-13. https://doi.org/10.19981/j.CN23-1581/G3.2024.13.003
Kar, A. K., & Dwivedi, Y. K. (2020). Theory building with big data-driven research—Moving away from the “What” towards the “Why.” International Journal of Information Management, 54, 102205. https://doi.org/10.1016/j.ijinfomgt.2020.102205
Kumar, S., Kar, A. K., & Ilavarasan, P. V. (2021). Applications of text mining in services management: A systematic literature review. International Journal of Information Management Data Insights, 1(1), 100008. https://doi.org/10.1016/j.ijinfomgt.2021.100008
Lu, Y. (2024). A study on tourist satisfaction of online OTA platforms based on text analysis: A case study of Ctrip.com. Journal of Xingtai College, 2, 83-92. Retrieved from https://kns.cnki.net/kcms2/article/abstract?v=cp4X_KT6XPjDmBHvdUiusKSZrSJ70wYSFlUfTSwfHWQeMzB83yM09JlqPy_7BPi0_F28zghiEReOuhp9-1wIo9p8St-UEgH3gjTYSVMY0zlyOcO82NNsYjQHu_vMFbZfXCVmaouhcJjg5xxoUUczixup_X_ORBnJ0VFV45lsoMbuTqNpg0LLj_IXFbcLMg2n9OxJc25MJQHLXjVSGyEoG6wg_3Vud&uniplatform=NZKPT&language=CHS
Mahr, D., Stead, S., & Odekerken-Schröder, G. (2019). Making sense of customer service experiences: A text mining review. Journal of Services Marketing, 33(1), 88-103. https://doi.org/10.1108/JSM-10-2018-0295
Martín, C. A., Torres, J. M., Aguilar, R. M., & Diaz, S. (2018). Using deep learning to predict sentiments: A case study in tourism. Complexity, 2018, Article 7408431. https://doi.org/10.1155/2018/7408431
Ministry of Tourism and Culture Malaysia. (2015, September 21). Achievements and recognitions. Retrieved September 5, 2015, from http://www.motac.gov.my/en/profile/achievements-and-recognitions
Mittal, D., & Agrawal, S. R. (2022). Determining banking service attributes from online reviews: Text mining and sentiment analysis. International Journal of Bank Marketing, 40(3), 558-577. https://doi.org/10.1108/IJBM-08-2021-0380
Mohammed, N. A. D. Z. I. R. A. H., Aziz, Y. A., Awang, K. W., & Samdin, Z. A. I. T. O. N. (2018). Influence of destination attractiveness on place satisfaction and environmentally responsible behavior in marine parks. Journal of Sustainability Science and Management, 5, 52-67. Retrieved from https://jssm.umt.edu.my/wp-content/uploads/sites/51/2020/05/5.15.1pdf.pdf
Papilaya, R. L. (2018, February). Effect of tourist characteristic, marine tourism demand, and number of visits to the value perceptions and willingness to pay to environmental marine tourism in Ambon City. IOP Conference Series: Earth and Environmental Science, 116(1), 012097. https://doi.org/10.1088/1755-1315/116/1/012097
Ren, X., & Zhao, G. (2024). Visitor perceptions of comprehensive parks in the city center of Guangzhou based on social media comments. Gardening, 6, 141-150. https://doi.org/10.12193/j.laing.2024.06.0141.016
Sabah Tourism Board. (2019). Tourism statistics. Retrieved February 21, 2020, from https://www.sabahtourism.com/statistics/
Su, Y., Xu, J., Sotiriadis, M., & Shen, S. (2021). Authenticity, perceived value and loyalty in marine tourism destinations: The case of Zhoushan, Zhejiang Province, China. Sustainability, 13(7), 3716. https://www.mdpi.com/2071-1050/13/7/3716
Sun, X., & Ni, R. (2018). Product awareness, emotional expression, and brand image perception of Chinese cruise tourists: A content analysis based on online reviews. Geographical Research, 6, 1159-1180. https://doi.org/10.11821/dlyj201806008
Tongcheng Travel Holdings Limited. (2024). Summer travel consumer trend report. Retrieved June 10, 2024, from http://www.ec100.cn/detail--6640430.html
Vetitnev, A., Chigarev, D., & Enushevskaya, V. (2021). Sentiment analysis as a tool for assessing the negative impact of tourism on a destination. In E3S Web of Conferences, 311, 06008). EDP Sciences. https://doi.org/10.1051/e3sconf/202131106008
Villarroel Ordenes, F., & Zhang, S. (2019). From words to pixels: Text and image mining methods for service research. Journal of Service Management, 30(5), 593-620. https://doi.org/10.1108/JOSM-08-2019-0254
Zhang, W., Tang, S., Chen, L., & Xu, M. (2024). A study on visitor perceptions of cultural heritage ecological environment and its impact on heritage tourism image based on network text analysis: A case study of the Ming City Wall in Nanjing. Ecological Economy, 6, 135-140. Retrieved from https://kns.cnki.net/kcms2/article/abstract?v=cp4X_KT6XN9DZQZoW6snP8Fpr4E8OIq2sGIMlDR9CVnHIC_IcluAwTXL5UMZwvV6iREKSrI3OZmkTFrRm1WAsXy05hd1EBi6zoCp02zQN8HajZpwhahD68WgwcghL1xBFvJdCSfVOcCxhl2SuphfTryw2EWurcj43sOQBG4uWufpLDGtnFJPoFGvS4Ct7ZEAkZINR50KtX2XghTslSa5MMGqKTkXmWv&uniplatform=NZKPT&language=CHS
_[eISSN___2504-8562]_-_Google_Scholar_-_Google_Chrome_30_11_2023_8_56_06_AM.png)
.png)
