Sentiment Classification of Climate Change and Tourism Content Using Support Vector Machine
-
Yerik Afrianto Singgalen
*
Atma Jaya Catholic University of Indonesia, Jakarta,
Indonesia
(*) Corresponding Author
Abstract
This research aims to classify public sentiment regarding the issue of climate change and tourism. The research problem addressed in this study pertains to the classification of public sentiment concerning climate change within the tourism sector. Specifically, the study aims to explore and classify the public's sentiments regarding the impact of climate change on tourism activities.The methodology employed is CRISP-DM, which encompasses stages of business understanding, data understanding, modeling, evaluation, and deployment. Specifically, the SVM and SMOTE algorithms are utilized in the modeling stage to achieve optimal results. By leveraging this systematic approach and advanced algorithms, the study seeks to comprehensively analyze public sentiment towards climate change within the context of tourism, thus contributing valuable insights to academia and industry practitioners. Applying CRISP-DM methodology coupled with SVM and SMOTE algorithms enhances the rigor and effectiveness of sentiment analysis in addressing the complexities of climate change discourse in the tourism sector. The findings of this research demonstrate that the SVM and SMOTE algorithms yield promising results in sentiment classification, with an accuracy of 86.15% +/- 1.68% (micro average: 86.15%), precision of 85.17% +/- 2.16% (micro average: 85.11%) (positive class: Positive), recall of 87.64% +/- 3.39% (micro average: 87.64%) (positive class: Positive), f_measure of 86.34% +/- 1.79% (micro average: 86.35%) (positive class: Positive), and AUC of 0.923 +/- 0.012 (micro average: 0.923) (positive class: Positive). These metrics indicate the effectiveness and reliability of the SVM and SMOTE algorithms in accurately classifying sentiment toward climate change in the context of tourism. The high accuracy, precision, recall, f_measure, and AUC scores suggest that the models produced by these algorithms are robust and capable of capturing nuanced sentiment patterns, thereby contributing to the advancement of sentiment analysis techniques in climate change research within the tourism domain.
Downloads
References
D. Navarro-Drazich et al., “Climate change and tourism in South and Central America,” J. Sustain. Tour., vol. 0, no. 0, pp. 1–17, 2023, doi: 10.1080/09669582.2023.2210783.
G. D. Sharma, B. Taheri, R. Chopra, and J. S. Parihar, “Relationship between climate change and tourism: an integrative review,” Serv. Ind. J., vol. 0, no. 0, pp. 1–28, 2023, doi: 10.1080/02642069.2023.2254714.
K. Dube et al., “Tourism and climate change in Africa: informing sector responses,” J. Sustain. Tour., vol. 0, no. 0, pp. 1–21, 2023, doi: 10.1080/09669582.2023.2193355.
F. Wolf et al., “Small island developing states, tourism and climate change,” J. Sustain. Tour., vol. 0, no. 0, pp. 1–19, 2022, doi: 10.1080/09669582.2022.2112203.
C. T. Cavaliere and L. J. Ingram, “Climate change and anger: misogyny and the dominant growth paradigm in tourism,” Ann. Leis. Res., vol. 26, no. 3, pp. 354–371, 2023, doi: 10.1080/11745398.2021.1949732.
S. Becken, E. Whittlesea, J. Loehr, and D. Scott, “Tourism and climate change: evaluating the extent of policy integration,” J. Sustain. Tour., vol. 28, no. 10, pp. 1603–1624, 2020, doi: 10.1080/09669582.2020.1745217.
M. Rutty, M. Hewer, N. Knowles, and S. Ma, “Tourism & climate change in North America: regional state of knowledge,” J. Sustain. Tour., vol. 0, no. 0, pp. 1–24, 2022, doi: 10.1080/09669582.2022.2127742.
A. Arabadzhyan, P. Figini, C. García, M. M. González, Y. E. Lam-González, and C. J. León, “Climate change, coastal tourism, and impact chains–a literature review,” Curr. Issues Tour., vol. 24, no. 16, pp. 2233–2268, 2021, doi: 10.1080/13683500.2020.1825351.
M. Alizadeh, R. Mirzaei, and A. Dittmann, “Climate change and its potential impacts on sustainable tourism development,” Anatolia, vol. 32, no. 3, pp. 443–455, 2021, doi: 10.1080/13032917.2021.1886130.
R. Steiger, N. Knowles, K. Pöll, and M. Rutty, “Impacts of climate change on mountain tourism: a review,” J. Sustain. Tour., vol. 0, no. 0, pp. 1–34, 2022, doi: 10.1080/09669582.2022.2112204.
C. Michael Hall and J. Saarinen, “20 years of Nordic climate change crisis and tourism research: a review and future research agenda,” Scand. J. Hosp. Tour., vol. 21, no. 1, pp. 102–110, 2021, doi: 10.1080/15022250.2020.1823248.
H. Zhao and A. Ewert, “College Students’ Knowledge and Perceptions of Tourism Climate Change Impacts: Do Major, Grade and Gender Matter?,” J. Hosp. Tour. Educ., vol. 33, no. 4, pp. 258–269, 2021, doi: 10.1080/10963758.2020.1727342.
D. Scott and S. Gössling, “From Djerba to Glasgow: have declarations on tourism and climate change brought us any closer to meaningful climate action?,” J. Sustain. Tour., vol. 30, no. 1, pp. 199–222, 2021, doi: 10.1080/09669582.2021.2009488.
L. Horne, S. De Urioste-Stone, P. Rahimzadeh Bajgiran, and E. Seekamp, “Understanding Tourism Suppliers’ Resilience to Climate Change in a Rural Destination in Maine,” Tour. Plan. Dev., vol. 0, no. 0, pp. 1–22, 2022, doi: 10.1080/21568316.2022.2083222.
R. Steiger, E. Posch, G. Tappeiner, and J. Walde, “Seasonality matters: simulating the impacts of climate change on winter tourism demand,” Curr. Issues Tour., vol. 26, no. 17, pp. 2777–2793, 2023, doi: 10.1080/13683500.2022.2097861.
W. Mushawemhuka, J. M. Fitchett, and G. Hoogendoorn, “Climate change and adaptation in the Zimbabwean nature-based tourism industry,” Anatolia, vol. 00, no. 00, pp. 1–12, 2022, doi: 10.1080/13032917.2022.2132412.
A. McCreary, E. Seekamp, L. R. Larson, J. Smith, and M. A. Davenport, “Climate Change and Nature-Based Tourism: How Do Different Types of Visitors Respond?,” Tour. Plan. Dev., 2020, doi: 10.1080/21568316.2020.1861079.
S. Wang, Y. Yu, J. Chen, and J. Liu, “Impact of climate change on cherry blossom viewing tourism: analysis and simulation based on Weibo proxy data,” Curr. Issues Tour., vol. 26, no. 5, pp. 718–734, 2023, doi: 10.1080/13683500.2022.2049711.
Y. A. Singgalen, “Analisis Sentimen Top 10 Traveler Ranked Hotel di Kota Makassar Menggunakan Algoritma Decision Tree dan Support Vector Machine,” KLIK Kaji. Ilm. Inform. dan Komput., vol. 4, no. 1, pp. 323–332, 2023, doi: 10.30865/klik.v4i1.1153.
Y. A. Singgalen, “Analisis Sentimen Wisatawan terhadap Kualitas Layanan Hotel dan Resort di Lombok Menggunakan SERVQUAL dan CRISP-DM,” Build. Informatics, Technol. Sci., vol. 4, no. 4, pp. 1870–1882, 2023, doi: 10.47065/bits.v4i4.3199.
Y. A. Singgalen, “Analisis Sentimen Konsumen terhadap Food , Services , and Value di Restoran dan Rumah Makan Populer Kota Makassar Berdasarkan Rekomendasi Tripadvisor Menggunakan Metode CRISP-DM dan,” Build. Informatics, Technol. Sci., vol. 4, no. 4, pp. 1899–1914, 2023, doi: 10.47065/bits.v4i4.3231.
Y. A. Singgalen, “Analisis Sentimen Wisatawan terhadap Taman Nasional Bunaken dan Top 10 Hotel Rekomendasi Tripadvisor Menggunakan Algoritma SVM dan DT berbasis CRISP-DM,” J. Comput. Syst. Informatics, vol. 4, no. 2, pp. 367–379, 2023, doi: 10.47065/josyc.v4i2.3092.
Y. A. Singgalen, “Penerapan CRISP-DM dalam Klasifikasi Sentimen dan Analisis Perilaku Pembelian Layanan Akomodasi Hotel Berbasis Algoritma Decision Tree ( DT ),” J. Sist. Komput. dan Inform., vol. 5, no. 2, pp. 237–248, 2023, doi: 10.30865/json.v5i2.7081.
Y. A. Singgalen, “Analisis Performa Algoritma NBC , DT , SVM dalam Klasifikasi Data Ulasan Pengunjung Candi Borobudur Berbasis CRISP-DM,” Build. Informatics, Technol. Sci., vol. 4, no. 3, pp. 1634–1646, 2022, doi: 10.47065/bits.v4i3.2766.
Y. A. Singgalen, “Analisis Perilaku Wisatawan Berdasarkan Data Ulasan di Website Tripadvisor Menggunakan CRISP-DM : Wisata Minat Khusus Pendakian Gunung Rinjani dan Gunung Bromo,” J. Comput. Syst. Informatics, vol. 4, no. 2, pp. 326–338, 2023, doi: 10.47065/josyc.v4i2.3042.
Y. A. Singgalen, “Analisis Sentimen Pengunjung Pulau Komodo dan Pulau Rinca di Website Tripadvisor Berbasis CRISP-DM,” J. Inf. Syst. Res., vol. 4, no. 2, pp. 614–625, 2023, doi: 10.47065/josh.v4i2.2999.
R. Obiedat et al., “Sentiment Analysis of Customers’ Reviews Using a Hybrid Evolutionary SVM-Based Approach in an Imbalanced Data Distribution,” IEEE Access, vol. 10, pp. 22260–22273, 2022, doi: 10.1109/ACCESS.2022.3149482.
D. Scott, N. L. B. Knowles, S. Ma, M. Rutty, and R. Steiger, “Climate change and the future of the Olympic Winter Games: athlete and coach perspectives,” Curr. Issues Tour., vol. 26, no. 3, pp. 480–495, 2023, doi: 10.1080/13683500.2021.2023480.
H. Rice, S. Cohen, D. Scott, and R. Steiger, “Climate change risk in the Swedish ski industry,” Curr. Issues Tour., vol. 25, no. 17, pp. 2805–2820, 2022, doi: 10.1080/13683500.2021.1995338.
A. Rai, D. P. Ayadi, B. Shrestha, and A. Mishra, “On the realities of gender inclusion in climate change policies in Nepal,” Policy Des. Pract., vol. 4, no. 4, pp. 501–516, 2021, doi: 10.1080/25741292.2021.1935643.
C. J. León, E. Giannakis, G. Zittis, D. Serghides, Y. E. Lam-González, and C. García, “Tourists’ Preferences for Adaptation Measures to Build Climate Resilience at Coastal Destinations. Evidence from Cyprus,” Tour. Plan. Dev., vol. 20, no. 6, pp. 973–999, 2023, doi: 10.1080/21568316.2021.1958914.
Y. Fang, A. Trupp, J. S. Hess, and S. Ma, “Tourism under climate crisis in Asia: impacts and implications,” J. Sustain. Tour., vol. 0, no. 0, pp. 1–17, 2022, doi: 10.1080/09669582.2022.2112202.
M. Sheller, “Reconstructing tourism in the Caribbean: connecting pandemic recovery, climate resilience and sustainable tourism through mobility justice,” J. Sustain. Tour., vol. 29, no. 9, pp. 1–14, 2020, doi: 10.1080/09669582.2020.1791141.
H. Olya, N. Kim, and M. J. Kim, “Climate change and pro-sustainable behaviors: application of nudge theory,” J. Sustain. Tour., vol. 0, no. 0, pp. 1–19, 2023, doi: 10.1080/09669582.2023.2201409.
D. Scott, N. Knowles, and R. Steiger, “Is snowmaking climate change maladaptation?,” J. Sustain. Tour., vol. 32, no. 2, pp. 282–303, 2022, doi: 10.1080/09669582.2022.2137729.
D. Zheng, C. Huang, and B. Oraltay, “Digital cultural tourism: progress and a proposed framework for future research,” Asia Pacific J. Tour. Res., vol. 28, no. 3, pp. 234–253, 2023, doi: 10.1080/10941665.2023.2217958.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Sentiment Classification of Climate Change and Tourism Content Using Support Vector Machine
Pages: 357-367
Copyright (c) 2024 Yerik Afrianto Singgalen
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
