Assessment of the Predictability of Heatwave Index Using ASOS and ERA5 Data with Machine Learning: Case Study of South Korea, 1979-2020

2021 ◽  
Vol 16 (2) ◽  
pp. 147-156
Author(s):  
Geunah Kim ◽  
◽  
Jonggu Kang ◽  
Yemin Jeong ◽  
Seoyeon Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
South Korea

scholarly journals Effects of the COVID-19 Pandemic on Classrooms: A Case Study on Foreigners in South Korea Using Applied Machine Learning

2021 ◽  
Vol 13 (9) ◽  
pp. 4986
Author(s):  
Imatitikua D. Aiyanyo ◽  
Hamman Samuel ◽  
Heuiseok Lim
Keyword(s):  
Machine Learning ◽  
South Korea ◽  
Sentiment Analysis ◽  
Statistical Significance ◽  
Machine Learning Techniques ◽  
Online Support ◽  
Course Materials ◽  
Applied Machine Learning ◽  
Learning Techniques

In this study, we qualitatively and quantitatively examine the effects of COVID-19 on classrooms, students, and educators. Using a new Twitter dataset specific to South Korea during the pandemic, we sample the sentiment and strain on students and educators using applied machine learning techniques in order to identify various topical pain points emerging during the pandemic. Our contributions include a novel and open source geo-fenced dataset on student and educator opinion within South Korea that we are making available to other researchers as well. We also identify trends in sentiment and polarity over the pandemic timeline, as well as key drivers behind the sentiments. Moreover, we provide a comparative analysis of two widely used pre-trained sentiment analysis approaches with TextBlob and VADER using statistical significance tests. Ultimately, we analyze how public opinion shifted on the pandemic in terms of positive sentiments about accessing course materials, online support communities, access to classes, and creativity, to negative sentiments about mental fatigue, job loss, student concerns, and overwhelmed institutions. We also initiate initial discussions about the concept of actionable sentiment analysis by overlapping polarity with the concept of trigger management to assist users in coping with negative emotions. We hope that insights from this preliminary study can promote further utilization of social media datasets to evaluate government messaging, population sentiment, and multi-dimensional analysis of pandemics.

Developing a model of home-based primary care in South Korea: A 1.5-year case study

2020 ◽  
Vol 40 (6) ◽  
pp. 1403-1428
Author(s):  
Chang-O Kim ◽  
Jongwon Hong ◽  
Mihee Cho ◽  
Eunhee Choi ◽  
Soong-nang Jang
Keyword(s):  
Primary Care ◽  
South Korea ◽  
Home Based Primary Care ◽  
Home Based
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