References
- S. D. Kim, T. Y. Seong & M. H. Lee. (2015). Impacts of Inauguration of Sejong Metropolitan Autonomous City on Population Migration Network in Neighboring Areas : Focused on Population Migration in Chungcheong Region. Journal of the Korean Regional Development Association, 27(5), 283-302.
- D. S. Kim, J. H. Jang & D. H. Lee. (2009). Analysis of Population Movement by Region, Journal of the Korea Development Economics, 15(1), 133-152.
- J. Kulshrestha, F. Kooti, A. Nikravesh & P. K. Gummadi. (2012). Geographic Dissection of the Twitter Network. ICWSM 2012, 202-209.
- M. Lenormand, B. Goncalves, A. Tugores & J. J. Ramasco. (2015). Human diffusion and city influence. Journal of The Royal Society Interface, 12(109), 20150473. DOI : 10.1098/rsif.2015.0473
- I. Y. Hong. (2015). Spatial Distribution of Korean Geotweets. Journal of the Korean Cartographic Association, 15(2), 93-101. https://doi.org/10.16879/jkca.2015.15.2.093
- Y. K. Cha. (2018). Spatial Characteristics of High-density Location-based Social Network Service Data: The Case of Tweet Data in Seoul. The Geographical Journal of Korea, 52(2), 257-267.
- Blanford, J. I., Huang, Z., Savelyev, A. & MacEachren, A. M. (2015). Geo-located tweets. Enhancing mobility maps and capturing cross-border movement. PloS one, 10(6). DOI : 10.1371/journal.pone.0129202
- Zagheni, E., Garimella, V. R. K., Weber, I. & State, B. (2014). Inferring international and internal migration patterns from twitter data. In Proceedings of the 23rd International Conference on World Wide Web, 439-444.
- Khan, S. F., Bergmann, N., Jurdak, R., Kusy, B. & Cameron, M. (2017). Mobility in cities: Comparative analysis of mobility models using Geo-tagged tweets in Australia. In 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA), 816-822. DOI : 10.1109/ICBDA.2017.8078751.
- Hawelka, B., Sitko, I., Beinat, E., Sobolevsky, S., Kazakopoulos, P. & Ratti, C. (2014). Geo-located Twitter as proxy for global mobility patterns. Cartography and Geographic Information Science, 41(3), 260-271. https://doi.org/10.1080/15230406.2014.890072
- Huang, Y., Li, Y. & Shan, J. (2018). Spatial-temporal event detection from geo-tagged tweets. ISPRS International Journal of Geo-Information, 7(4), 150. DOI : 10.3390/ijgi7040150.
- Cvetojevic, S. & Hochmair, H. H. (2018). Analyzing the spread of tweets in response to Paris attacks. Computers, Environment and Urban Systems, 71, 14-26. DOI : 10.1016/j.compenvurbsys.2018.03.010.
- J. H. Cho & I. J. Seo. (2016). Comparing the Spatial Mobility of Residents and Tourists by using Geotagged Tweets. Journal of Information Technology Services, 15(3), 211-221. DOI : 10.9716/KITS.2016.15.3.211
- Lenormand, M., Goncalves, B., Tugores, A. & Ramasco, J. J. (2015). Human diffusion and city influence. Journal of The Royal Society Interface, 12(109), 473. DOI : 10.1098/rsif.2015.0473.
- Soliman, A., Yin, J., Soltani, K., Padmanabhan, A. & Wang, S. (2015). Where Chicagoans tweet the most: Semantic analysis of preferential return locations of Twitter users, In Proceedings of the 1st International ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics. ACM, 55-58. DOI : 10.1145/2835022.2835032.
- Leetaru, K., Wang, S., Cao, G., Padmanabhan, A. & Shook, E. (2013). Mapping the global Twitter heartbeat: The geography of Twitter. First Monday, 18(5).
- C. Y. Ku. (2018). Spatial Characteristics of High-density Location-based Social Network Service Data: The Case of Tweet Data in Seoul. The Geographical Journal of Korea, 52(2), 257-267.
- Li, L., Goodchild, M. F. & Xu, B. (2013). Spatial, temporal, and socioeconomic patterns in the use of Twitter and Flickr. Cartography and geographic information science, 40(2), 61-77. DOI : 10.1080/15230406.2013.777139.
- BTS. (Accessed 13 June 2019) Air Passenger Travel Arrivals in the United States from Selected Foreign Countries. https://www.bts.gov/content/air-passenger-travel-arrivals-united-states-selected-foreign-countries-thousands-passengers
- J. H. Oh. (2010). A Comparative Study on the Aerospace Body Inspection System in the United States, Europe and Korea. Conference of Aerospace Medical, 45-46.
- J. H. Cho & I. J. Seo. (2017). Investigation of Twitter Users' Activity Radius and Home Region in the City: The Case of Las Vegas. Journal of Korean Institute of Communications and Information Sciences, 42(2), 505-513. DOI : 10.7840/kics.2017.42.2.505
- M. G. Kim. (2016). A Study on Twitter User's Residential Location Inference for Twitter Mining, Ph.D. Thesis. University of Seoul.