• Title/Summary/Keyword: COVID-19 Epidemic Stress

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Sentiment Analysis for COVID-19 Vaccine Popularity

  • Muhammad Saeed;Naeem Ahmed;Abid Mehmood;Muhammad Aftab;Rashid Amin;Shahid Kamal
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.5
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    • pp.1377-1393
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    • 2023
  • Social media is used for various purposes including entertainment, communication, information search, and voicing their thoughts and concerns about a service, product, or issue. The social media data can be used for information mining and getting insights from it. The World Health Organization has listed COVID-19 as a global epidemic since 2020. People from every aspect of life as well as the entire health system have been severely impacted by this pandemic. Even now, after almost three years of the pandemic declaration, the fear caused by the COVID-19 virus leading to higher depression, stress, and anxiety levels has not been fully overcome. This has also triggered numerous kinds of discussions covering various aspects of the pandemic on the social media platforms. Among these aspects is the part focused on vaccines developed by different countries, their features and the advantages and disadvantages associated with each vaccine. Social media users often share their thoughts about vaccinations and vaccines. This data can be used to determine the popularity levels of vaccines, which can provide the producers with some insight for future decision making about their product. In this article, we used Twitter data for the vaccine popularity detection. We gathered data by scraping tweets about various vaccines from different countries. After that, various machine learning and deep learning models, i.e., naive bayes, decision tree, support vector machines, k-nearest neighbor, and deep neural network are used for sentiment analysis to determine the popularity of each vaccine. The results of experiments show that the proposed deep neural network model outperforms the other models by achieving 97.87% accuracy.

Analysis of News Agenda Using Text mining and Semantic Network Analysis: Focused on COVID-19 Emotions (텍스트 마이닝과 의미 네트워크 분석을 활용한 뉴스 의제 분석: 코로나 19 관련 감정을 중심으로)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.47-64
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    • 2021
  • The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

A Study on the Skin Stress Recognition and Beauty Care Status due to Wearing Masks (안면 마스크 착용에 따른 피부 스트레스 인식도와 뷰티 케어 현황에 관한 연구)

  • Kim, Hyeon-Suk
    • Journal of the Korean Applied Science and Technology
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    • v.38 no.2
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    • pp.465-475
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    • 2021
  • This study conducted an online and offline survey of 210 people from March 11 to 27, 2021 for the purpose of investigating and analyzing the current status of skin stress recognition and beauty care behavior due to wearing masks. The collected data were analyzed using SPSS 25.0 with Cronbach's α, Frequency Analysis, Chi-square test, and One way Anova. The average daily mask wearing time of more than 7 hours during the Covid-19 period was 43.8%, and skin stress recognition by wearing masks was highest among those in their 30s (M=4.27) and service workers (M=4.64), and those with acne and skin troubles (M=4.47) perceived high stress. The most important factor for home care treatment was cleansing(67.6%) and for beauty care was skin care(36.7%). Considerations factors on beauty care were 54.3% for service and customer care capabilities, and on body shape management method 45.7% for exercise. According to this study, respondents are recognizing skin stress due to the long-term use of masks, and home care treatment has been increasing as the esthetic salon has become unstable to visit due to the Covid-19 epidemic.

Characteristics of Job Stress Factors in Delivery Workers (택배종사자의 직무스트레스 요인 특성에 관한 연구)

  • Sejung Lee;Sangeun Jin;Seong Rok Chang
    • Journal of the Korean Society of Safety
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    • v.38 no.4
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    • pp.32-38
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    • 2023
  • Job stress factors are factors that induce biological, psychological, and behavioral responses in individuals when they encounter mental and physical stimuli in the workplace. According to occupational safety and health standards, employers are responsible for the health consequences of job stress when workers engage in activities that result in high levels of physical fatigue and mental stress. Such activities include long working hours, shift work (including night shifts), driving vehicles, and operating precision machinery. Therefore, precautionary measures should be implemented. Following the COVID-19 epidemic, the logistics industry in Korea has experienced rapid growth owing to the shift from offline to online platforms facilitated by advanced digital infrastructure. Consequently, this study conducted a survey to analyze job stress factors among delivery workers. The survey utilized a Korean job stress factor assessment tool comprising 43 items and analyzed job stress factors considering the work characteristics of the courier business field obtained from responses provided by 421 courier workers nationwide. The survey analysis revealed that the physical environment, job demands, and job autonomy exhibited higher stress indices among Korean workers. Furthermore, the younger the age, the higher the stress on job demands, whereas the higher the age, the higher the stress on relationship conflict, job instability, and workplace culture. In addition, daytime delivery work was associated with higher stress levels in job demands and job instability compared with nighttime delivery work. These findings can serve as foundational data for reducing and preventing job stress among courier workers, whose workload has increased owing to the growth of the logistics industry.

The Effect of the Transmission of Coronavirus Disease-2019 on the Mentality of Parents and Children After the First Wave of Infections (1차 확산기 이후 코로나바이러스감염증-2019의 전파가 부모와 아동의 심리에 미치는 영향)

  • Kim, Jeongyeon;Lee, Koeun;Nam, Okhyung;Lee, Hyo-seol;Choi, Sungchul;Kim, Kwangchul;Kim, Misun
    • Journal of the korean academy of Pediatric Dentistry
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    • v.48 no.3
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    • pp.269-279
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    • 2021
  • The purpose of this study is to evaluate the effect of the spread of a new type of coronavirus infection (COVID-19) on the mental state in school-age children and parents focusing on the aspects of sleep disorders and depression. A questionnaire survey was conducted for 123 parents and 108 school-age children who visited Department of Pediatric Dentistry, Kyung Hee University Dental Hospital at Gangdong from April 2, 2020 through April 25, 2020, via the direct writing method. Participants were assessed with Pittsburgh Sleep Quality Index, Generalized Anxiety Disorder (GAD)-7, Center for Epidemiology Scale for Depression. Logistic regressions were used with a level of significance of 5%. The prevalence of GAD, depression, and poor sleep in parents were 34.1%, 17.1% and 44.7%, respectively. The prevalence of GAD in children was 20.4%. Logistic regression showed that stress from Emergency Alert Messages about COVID-19 was associated with GAD and depression in parents. In children, the degree of emotional change after COVID-19 was associated with GAD. This study confirmed that there was a change in the psychological status of children and guardians due to the epidemic of coronavirus disease-2019, and it would be necessary to consider their psychological status during dental treatment.