• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.202-206
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• 2023

Today, social media has become a vital tool. The world communicates and reaches the news and each other's opinions through social media accounts. Recently, considerable research has been done on analyzing social media due to its rich data content. At the same time, since the beginning of the COVID-19 pandemic, which has afflicted so many around the world, the search for a vaccine has been intense. There have been many studies analyzing people's feelings during a crisis. This study aims to understand people's opinions about available Coronavirus vaccines through a learning model that was developed for this purpose. The dataset was collected using Twitter's streaming Application Programming Interface (API) , then combined with another dataset that had already been collected. The final dataset was cleaned, then analyzed using Python. Polarity and subjectivity functions were used to obtain the results. The results showed that most people had positive opinions toward vaccines in general and toward the Pfizer one. Our study should help governments and decision-makers dispel people's fears and discover new symptoms linked to those listed by the World Health Organization.

• The Journal of Korean Medicine
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• v.43 no.2
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• pp.124-139
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• 2022

Objectives: This study examined the effectiveness of Korean medical treatment for two patients complaining of discomfort after receiving Pfizer COVID-19 vaccine. Methods: The patients were hospitalized for 50 days and 12 days, respectively. They were treated with herbal medicine, acupuncture, electroacupuncture, and moxibustion. We used the Numerical Rating Scale (NRS) on numbness in extremities and headache, Manual Muscle Testing Grading System (MMT), Criteria for Sweating Categorization, and 36-Item Short Form Health Survey (SF-36) to evaluate the clinical effects of the treatment. Results: In Case 1, headache improved from peak NRS 9 and average NRS 7 on admission day to both NRS 3 on discharge. The SF-36 score was also increased, suggesting that the quality of life was improved. In Case 2, numbness in the extremities improved from NRS 8 on the day before admission to NRS 2 on discharge, and general condition also improved. Conclusions: This study suggests that Korean medicine can be an effective treatment for patients who experience long-lasting discomfort after being vaccinated with COVID-19, but with no abnormal findings in the examination.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.113-128
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• 2021

In this study, we aimed to understand the public opinion on COVID-19 vaccine. To achieve the goal, we analyzed COVID-19 vaccine-related Twitter posts. 45,413 tweets posted from March 16, 2020 to March 15, 2021 including COVID-19 vaccine names as keywords were collected. The 12 vaccine names used for data collection included 'Pfizer', 'AstraZeneca', 'Modena', 'Jansen', 'NovaVax', 'Sinopharm', 'SinoVac', 'Sputnik V', 'Bharat', 'KhanSino', 'Chumakov', and 'VECTOR' in the order of the number of collected posts. The collected posts were analyzed manually and automatedly through keyword analysis, sentiment analysis, and topic modeling to understand the opinions for the investigated vaccines. According to the results, there were generally more negative posts about vaccines than positive posts. Anxiety about the aftereffects of vaccination and distrust in the efficacy of vaccines were identified as major negative factors for vaccines. On the contrary, the anticipation for the suppression of the spread of coronavirus following vaccination was identified as a positive social factor for vaccines. Different from previous studies that investigated opinions about COVID-19 vaccines through mass media data such as news articles, this study explores opinions of social media users using keyword analysis, sentiment analysis, and topic modeling. In addition, the results of this study can be used by governmental institutions for making policies to promote vaccination reflecting the social atmosphere.