References
- Airportal (https://www.airportal.go.kr)
- Ahn, K. A (2017). Analysis of the Effects of the Exchange Rate Volatility on Marine and Air Transportation. Korea Trade Review, 42(6), 131-154. https://doi.org/10.22659/KTRA.2017.42.6.131
- Blei, D. M., A. Y. Ng and M. I. Jordan (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 993-1022.
- Cho, M. K. and Lee, B. J (2021). Comparison of service quality of full service carriers in Korea using topic modeling: based on reviews from TripAdvisor. Journal of Hospitality and Tourism Studies, 23(1), 152-165. https://doi.org/10.31667/jhts.2021.2.86.152
- Cho, C. H., S. H. Ahn, B. M. Park and S. M. Im (2012). Estimate and Forecast Air Freight Rates Using Stepwise Regression (From Incheon to LA and Frankfurt). Korea Research Academy of Distribution and Management Review, 15(2), 17-26.
- Choi, D. H., B. M. Song, D. H. Park and S. W. Lee (2022). Keyword trends analysis related to the aviation industry during the Covid-19 period using text mining. Journal of the Korea Industrial Information Systems Research, 27(2), 115-128. https://doi.org/10.9723/JKSIIS.2022.27.2.115
- Choi, H (2021). Stock prediction analysis through artificial intelligence using big data. Journal of the Korea Institute of Information and Communication Engineering, 25(10), 1435-1440. https://doi.org/10.6109/JKIICE.2021.25.10.1435
- Choi, J. H and Shin, C. S (2015). Correlation Analysis with Volume of Recreational Forest Visitors and Internet Search Words Using 'Big Data'. Journal of the Korean Institute of Forest Recreation, 19(4), 13-23. https://doi.org/10.34272/forest.2015.19.4.002
- Ham, S. K., H. J. Kim and Y. W. Kim (2021). A Big-Data Analysis of Media Coverage on COVID-19 : Topic Modeling and Semantic Network Analyses by Issue Cycle and Political Orientation. Korean Journal of Journalism & Communication Studies, 65(1), 148-189. https://doi.org/10.20879/kjjcs.2021.65.1.148
- IATA (https://www.iata.org/en)
- Incheon International Airport (www.airport.kr)
- Jeong, P. J., T. T. Zhao and H. S. Lee (2020). Analysis of Changes in the Air Passenger Transport Network by the Spread of COVID-19 -Focusing on International Airports in Asia-. Korea Logistics Review, 30(5), 119-136. https://doi.org/10.17825/klr.2020.30.5.119
- Jeong, P. J., T. T. Zhao and H. S. Lee (2020). A study on the Change of International Air Cargo Networks at Asian Airports by the COVID-19 Pandemic. Aviation Management Society of Korea, 18(4), 71-87.
- Jin, H. G., U. G. Guk and K. W. Kang (2002). Air Cargo Demand Forecasting using Time Series Data. Proceedings of the KOR-KST Conference, 42(), 1-5.
- Korea Audit Bureau of Certification (http://www.kabc.or.kr)
- KITA (www.kita.net)
- Korea Customs Logistics Association (www.kcla.kr)
- Ko, M. H. (2021). A Study on Travel Bubble after Covid-19 Using Text Mining., The Korea Academic Society of Tourism and Leisure Academic presentation proceedings, 33-43.
- Kim, K. I. (2017). A Study on the Analysis and Prediction of Factors Determining Freight Rates for Korea's Airplane Export: Focusing on the L.A. Route in the United States and Frankfurt Route in Europe, Inha University Logistics Graduate School Master's or Doctoral Thesis.
- Kim, D. Y and Lee, Y. I (2018). News based Stock Market Sentiment Lexicon Acquisition Using Word2Vec, The Korea Journal of BigData, 3(1), 13-20. https://doi.org/10.36498/kbigdt.2018.3.1.13
- Kim, D. H and Cho, H. S (2020). An Empirical Study on Determinants of Freight Fluctuation in Air Transportation. The Journal of shipping and logistics, 36(2), 161-180. https://doi.org/10.37059/TJOSAL.2020.36.2.161
- Kim, M. S (2001), A study on forecasting air passenger demand, Journal of Aviation Development of Korea, (2), 102-135.
- Kim, M. G., J. H. Ryu., D. H. Cha and M. K. Sim (2020). Stock Price Prediction Using Sentiment Analysis: from "Stock Discussion Room" in Naver, The Journal of Society for e-Business Studies, 25(4), 61-75.
- Kim, J. O and Kwon, C. H (2020). Comparative Analysis of News Articles related to Airlines and Staff the Previous Corona19(2019) and After Corona19(2020), Journal of the Korea Society of Computer and Information, 25(7), 167-173. https://doi.org/10.9708/JKSCI.2020.25.07.167
- Kim, J. C., H. G. Son and J. S. Park (2019). A Study on International Air Demand Forecasting by ARIMA-Intervention Model. Journal of Korean Society of Transportation, 37(1), 51-65. https://doi.org/10.7470/jkst.2019.37.1.051
- Kim, H. J., N. O. Jo and K. S. Shin (2015), Text Mining-Based Emerging Trend Analysis for the Aviation Industry. Journal of Intelligence and Information Systems, 21(1), 65-82. https://doi.org/10.13088/jiis.2015.21.1.65
- Kim, H. N., K. S. Lee and G. S. Jo (2003). Document Classification using Weighted Associative Classifier. Korea Institute of Information Scientists and Engineers, Academic presentation proceedings, 30(2), 154-163.
- Lee, M. C and Kim. H. J (2018). Construction of Event Networks from Large News Data Using Text Mining Techniques. Journal of Intelligence and Information Systems, 24(1), 183-203.
- Lee, J. Y and Ryu, J. P (2021). Prediction of Housing Price Index Using Artificial Neural Network. Journal of the Korea Academia-Industrial cooperation Society, 22(4), 228-234.
- Lim, J. P (2022). Analysis of air demand recovery and paradigm shift of the air transport industry after COVID-19. International Journal of Tourism and Hospitality Research, 36(2), 167-181. https://doi.org/10.21298/IJTHR.2022.2.36.2.167
- Min, K. C and Ha, H. K (2020). Forecasting the Daily Demand of Air Cargo Using Data Mining with CHAID Approach. Journal of Korean Society of Transportation, 38(3), 190-207. https://doi.org/10.7470/jkst.2020.38.3.190
- Moon, H. N and Kim, J. W (2014). A study on an individual stock return prediction model using internet news. Korea Intelligent Information System Society Academic presentation proceedings, 387 - 393.
- Park, G. Y and An, H. J (2019). The Topic Modeling Analysis of The DMZ Tour Issues Using Text Mining. Journal of Tourism and Leisure Research, 31(4), 143-159. https://doi.org/10.31336/JTLR.2019.4.31.4.143
- Park, N. H and Kim, H. B (2016). The Effect of Keywords of Internet Search Engines on the Demand of Chinese Inbound Tourists: An Application of the Baidu Index Data. Journal of Tourism Sciences, 40(3), 159-174. https://doi.org/10.17086/JTS.2016.40.3.159.174
- Park, J. C., K. J. Han and H. Y. Chae (2019). Correlation Analysis between Livestock Mortality Caused by Heat Wave and News Big Data. Journal of the Association of Korean Geographers, 8(3), 529-543. https://doi.org/10.25202/JAKG.8.3.13
- Park, J. S and Lee, J. S (2021). Predictability of Housing Sales Prices Employing a Real Estate Sentiment Index : Using Unstructured Big Data of Online Newspaper and TV Broadcast News. Journal of Korea Planning Association, 56(4), 99-111.
- Rha, J. S (2022). Analysis of Factors Affecting Surge in Container Shipping Rates in the Era of Covid19 Using Text Analysis. Journal of the Korea Industrial Information Systems Research, 27(1), 111-123. https://doi.org/10.9723/JKSIIS.2022.27.1.111
- Rha, J. S (2020). Analysis on Issues Related to Supply Chain Management in the Era of Covid19 using Network Text Analysis. Journal of the Korea Industrial Information Systems Research, 25(6), 109-123. https://doi.org/10.9723/JKSIIS.2020.25.6.109
- Seo, S. K., B. H. Jung and I. K. Kim (2009). A Study on Estimating of Air Freight Demand using Regression Model. Journal of the Military Operations Research Society of Korea (MORS-K), 35(3), 1-15.
- Seo, S. S., J. W. Park., G. S. Song and S. G. Jo (2014). A Study of Air Freight Forecasting Using the ARIMA Model. Journal of Distribution Science, 12(2), 59-71. https://doi.org/10.15722/jds.12.2.201402.59
- Stevens, K., P. Kegelmeyer, D. Andrzejewski and D. Buttler (2012). Exploring topic coherence over many models and many Paper presented at the 2012 joint conference on empirical methods in natural language processing and computational language learning of the Association for Computational Linguistics, 952-961.
- Yoo, H. S and Kim, K. S (2021). A Study on Correlation Between COVID-19 and Postal Logistics Keyword Volume Using Machine Learning Techniques. Proceedings of KIIT Conference, 242-245