Acknowledgement
이 논문은 2021년 대한민국 교육부와 한국연구재단의 지원을 받아 수행된 연구임 (NRF-2021S1A5C2A02088387).
References
- Cho, Seunghan (2021. July 8). Although the fatality rate has decreased, it has increased as it penetrates the younger generation...The difference between the 4th and 1st trends. Dongascience, Available: https://www.dongascience.com/news.php?idx=47789
- Kim, Donghun, Oh, Chanhee, & Zhu, Yongjun (2021). Analyzing research trends in blockchain studies in South Korea using dynamic topic modeling and network analysis. Korean Society for Information Society, 38(3), 23-39. https://doi.org/10.3743/KOSIM.2021.38.3.023
- Kim, Hyunjoong (2018). customized-KoNLPy (0.0.64) Avalilable: https://pypi.org/project/customized-KoNLPy/
- Kim, Jinsol, Shin, Donghoon, & Kim, Heewoong (2021). Analysis of major COVID-19 issues using unstructured big data. The Knowledge Management Society of Korea, 22(2), 145-165. https://doi.org/10.15813/kmr.2021.22.2.008
- Korea Insight Institute (2020). COVID-19 and Hate Pandemic(11-1620000-000785-01). National Human Rights Commission of Korea.
- Kwon, Namyoung (2020. April 26). Patient 31 of Daegu's "Super Spreader" Shincheonji Church discharged after 67 days. KukMinIlbo, Available: http://news.kmib.co.kr/article/view.asp?arcid=0014518605&code=61121911&cp=nv
- Lee, Eunhee (2021). United nations guidance note on addressing and countering COVID-19 related hate speech. Democratic Legal Studies Association, 75, 213-221. https://doi.org/10.15756/dls.2021..75.213
- Lee, Haengmi (2021). Korean novels after COVID-19 and the threshold of disgust. Journal of Modern Korean Literature, 22(2), 49-90.
- Lee, Jiesung (2020). COVID-19, an ethical task towards 'Fear' and 'Disgust' of N-Po Generation. The Korean Journal of Chiristian Social Ethics, 48, 107-133. https://doi.org/10.21050/CSE.2020.48.04
- Lee, Jongwon (2020). The social problem caused by COVID-19 and the suggested solutions. University and Christian Mission, 45, 61-90. https://doi.org/10.22737/U&M.2020.45.061
- Lim, Yooha (2021). COVID-19 blues: a big data analysis. The Korean Journal of Counseling and Psychotherapy, 33(2), 829-852. https://doi.org/10.23844/kjcp.2021.05.33.2.829
- Ministry of Foreign Affairs Republic of Korea (2021. December 14). Special travel warning issued for overseas travel across countries and regions. Available: https://www.mofa.go.kr/
- Ministry of Health and Welfare (2020a. March 21). Coronavirus infection-19 outbreak status in Korea. Available: http://ncov.mohw.go.kr/
- Ministry of Health and Welfare (2020b. April 21). Coronavirus infection-19 outbreak status in Korea. Available: http://ncov.mohw.go.kr/
- Ministry of Health and Welfare (2020c. December 31). The current status of COVID-19 outbreak in Korea (regular briefing). Available: http://ncov.mohw.go.kr/
- Ministry of Health and Welfare (2022a. January 18). Coronavirus infection-19 outbreak status in Korea. Available: http://ncov.mohw.go.kr/
- Ministry of Health and Welfare (2022b. January 18). Coronavirus infection-19 overseas outbreak status. Available: http://ncov.mohw.go.kr/
- Park, Eunjeong & Cho, Sungzoon (2014). KoNLPy: Korean natural language processing in Python. Proceedings of the 26th Annual Conference on Human and Cognitive Language Technology, Chuncheon, 133-136.
- Park, Sangmi (2020). The impact of the COVID-19 pandemic on mental health among population. Korean Journal of Health Education and Promotion, 37(5), 83-91. http://dx.doi.org/10.14367/kjhep.2020.37.5.83
- Shon, Dallim (2020). A study on the expressions used in COVID-19 news: focusing on fear and hate reflected in headlines. Journal of Ewha Korean Language and Literature, 51, 137-166. https://doi.org/10.29190/JEKLL.2020.51.137
- Yoo, Yunjoo & Yeo, Jungsung (2020). Consumer anxiety about masks in the context of COVID-19. Consumer Policy and Education Review, 16(4), 127-153. https://doi.org/10.15790/cope.2020.16.4.127
- Akram, W. & Kumar, R. (2017). A study on positive and negative effects of social media on society. International Journal of Computer Sciences and Engineering, 5(10), 351-354. https://doi.org/10.26438/ijcse/v5i10.351354
- Alowibdi, J. S., Alshdadi, A. A., Daud, A., Dessouky, M. M., & Alhazmi, E. A. (2021). Coronavirus pandemic (COVID-19): emotional toll analysis on twitter. International Journal on Semantic Web and Information Systems (IJSWIS), 17(2), 1-21. http://doi.org/10.4018/IJSWIS.2021040101
- Antoci, A., Delfino, A., Paglieri, F., Panebianco, F., & Sabatini, F. (2016). Civility vs. incivility in online social interactions: an evolutionary approach. PloS One, 11(11), e0164286. https://doi.org/10.1371/journal.pone.0164286
- Badjatiya, P., Gupta, S., Gupta, M., & Varma, V. (2017). Deep learning for hate speech detection in tweets. In Proceedings of the 26th international conference on World Wide Web companion, Perth, Australia. https://doi.org/10.1145./3041021.3054223
- Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. Proceedings of the Third International ICWSM Conference, 361-362. https://doi.org/10.13140/2.1.1341.1520
- Blei, D. M. & Lafferty, J. D. (2006). Dynamic Topic Models: Proceedings of the 23rd international conference on Machine learning, ACM Other Conferences. https://doi.org/10.1145/1143844.1143859
- Chen, G. M., Muddiman, A., Wilner, T., Pariser, E., & Stroud, N. J. (2019). We should not get rid of incivility online. Social Media + Society, 5(3). https://doi.org/10.1177/2056305119862641
- Choi, D. H. (2021). The multifaceted impact of social media on risk, behavior, and negative emotions during the COVID-19 outbreak in South Korea. Asian Journal of Communication, 31(5), 337-354. https://doi.org/10.1080/01292986.2021.1968447
- Hopkins, E. E., Spadaro, K. C., Walter, L., Wasco, J. J., Fisher, M., & Sterrett, S. E. (2017). Incivility in the online classroom: a guide for policy development. Nursing Forum, 52(4), 306-312. https://doi.org/10.1111/nuf.12205
- JustAnotherArchivist (2020). snscrape (0.3.4) [Online App]. https://github.com/JustAnotherArchivist/snscrape
- Kim, B. (2020). Effects of social grooming on incivility in COVID-19. Cyberpsychol Behav Soc Netw, 23(8), 519-525. https://doi.org/10.1089/cyber.2020.2021
- Kim, B., Cooks, E., & Kim, S.K. (2022). Exploring incivility and moral foundations toward asians in english-speaking tweets in hate crime-reporting cities during the COVID-19 pandemic, Internet Research, 32(1), 362-378. https://doi.org/10.1108/INTR-11-2020-0678
- Linton M., Teo, E. G. S., Bommes E., Chen, C.Y., Hardle, W. K. (2017). Dynamic Topic Modelling for Cryptocurrency Community Forums. In: Hardle W., Chen CH., Overbeck L. (eds). Applied Quantitative Finance. Statistics and Computing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54486-0_18
- Rehurek, R. & Sojka, P. (2011). Gensim--python framework for vector space modelling. NLP Centre, Faculty of Informatics, Masaryk University, Brno, Czech Republic, 3(2).
- Wang, Y., Hao, H., & Platt, L.S. (2021). Examining risk and crisis communications of government agencies and stakeholders during early-stages of COVID-19 on Twitter. Computers in Human Behavior, 114, 106568. http://doi.org/10.1016/j.chb.2020.106568.
- Xiong, F. & Liu, Y. (2014). Opinion formation on social media: an empirical approach. Chaos: An Interdisciplinary Journal of Nonlinear Science, 24(1), 013130. https://doi.org/10.1063/1.4866011
- Yustiawan, Y., Maharani, W., & Gozali, A. A. (2015). Degree centrality for social network with opsahl method. Procedia Computer Science, 59, 419-426. https://doi.org/10.1016/j.procs.2015.07.559