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.

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

2. 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.
ABSTRACT
COVID-19
|
2020

3. 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.
INTRODUCTION
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. Parts of Speech
Tagging
Text Clean-up
Tokenization
Sentiment
Analysis
Emotion
Analysis
Keyword
Extraction
MODERNA
PFIZER

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/