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COVID-19 case study Presentation

In this case study, we will examine all tweets related to covid vaccines using sentiment analysis to evaluate the public sentiments towards the COVID-19 vaccines.<br>

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COVID-19 case study Presentation

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  1. COVID-19 Vaccines: PFIZER VS MODERNA CASE STUDY Analysis of public sentiments towards the COVID-19 vaccines.and guidelines

  2. ABSTRACT The widespread COVID-19 pandemic imposed enormous burdens and severely upset societies and economies worldwide. Medical institutions and healthcare professionals diverted all their efforts towards developing vaccines to combat the virus. In this case study, we will examine all tweets related to covid vaccines using sentiment analysis to evaluate the public sentiments towards the COVID-19 vaccines. COVID-19 | 2020

  3. INTRODUCTION The COVID-19 vaccination is currently a highly debated topic on social media platforms and news. In this research, we use Twitter data to analyze and evaluate the public sentiments towards the COVID-19 vaccination This research will help government officials and policymakers understand the public sentiment and assist in planning effective measures to conduct successful mass vaccination drives. COVID-19 | 2020

  4. DATA SOURCES: TWITTER DATA SCRAPED USING THE TWITTER API DATA TYPE: COVID VACCINES RELATED TWEETS COVID-19 | 2020

  5. THE ANALYZED TWEETS WERE SCRAPED BETWEEN 3RD MARCH AND 6TH APRIL. 1 MILLION COIVID VACCINE-RELATED TWEETS

  6. KEYWORDS USED TO EXTRACT DATA: COVID-19 | 2020 PFIZER VACCINE MODERNA VACCINE COVID VACCINE

  7. Text Clean-up PFIZER Sentiment Analysis Tokenization Emotion Analysis MODERNA Parts of Speech Tagging Keyword Extraction

  8. TEXT ANALYSIS MODELS APPLIED

  9. SENTIMENT ANALYSIS We used the sentiment analysis solution to evaluate the overall public sentiment of the US citizens towards the Pfizer and Moderna vaccines.

  10. TOPIC LABELING We will be using the model to identify the most discussed topics related to the Pfizer and Moderna vaccines on Twitter.

  11. KEYWORD EXTRACTION We will use the keyword extraction model to automate the identification and extraction of the most used keywords in the tweets related to the Pfizer and Moderna vaccine posted the US citizens.

  12. EMOTION ANALYSIS We will use emotion analysis to classify tweets as per the emotion expressed in the text. This will help in better understanding the thoughts of the general public when it comes to Pfizer or Moderna COVID-19 vaccines.

  13. Findings Pfizer VS Moderna Sentiment Analysis The analysis states that most of the users tweeted negative sentiments for both the vaccines. Although, tweets related to Pfizer were more negative when compared to the tweets for the Moderna vaccine.

  14. Findings Pfizer VS Moderna Emotion Analysis As for tweets related to Moderna, most tweets expressed fear. The second dominant emotion expressed in the tweets is happiness.

  15. Findings COVID vaccination tweets sentiment analysis The most dominant sentiment expressed in the tweets is negative. Over 59% of the tweets express negative feelings about vaccination

  16. Findings COVID vaccination tweets emotion analysis For emotion analysis, the most prevalent emotion expressed in the tweets is fear. Over 53% of users expressed fear in their tweets followed by happiness, sadness anger, and neutral emotion. The least expressed emotion in the analyzed tweets was love

  17. CONCLUSION The study was conducted to analyze the overall sentiments of US citizens in relation to COVID vaccination. The study shows people expressing more positive sentiments for the Pfizer vaccine in comparison to the Moderna Vaccine. As for emotions, fear and happiness were the most prevalent kind. The most expressed emotion for the Moderna vaccine was fear. As for the Pfizer vaccine, the most expressed emotion was happiness.

  18. READ THE FULL DETAILED BLOG AT WWW.BYTESVIEW.COM/ BLOG/COVID-19- VACCINES-CASE- STUDY/

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