Sentiment Towards the Covid-19 Vaccine

Stacy Fortes, Dr. Daehan Kwak, School of Computer Science and Technology, Kean University 1000 Morris Ave, Union, NJ 07083

Since March of 2020, when people began quarantining due to Covid-19, people have been waiting for life to go back to normal. This may soon be possible with the recent CDC announcement of Covid-19 vaccines. However, many people have pushed back against the vaccines due to the uncertainty of their effectiveness and/or side effects. Vaccine hesitancy leads to negative impacts and real threats to public health. Therefore, this study looks to determine the sentiment towards two Covid-19 vaccines, Pfizer and Moderna, via Twitter to understand the attitudes towards them in the United States. This study uses a Python script to collect data through Twitter’s API, Tweepy, in order to pick up on tweets regarding the vaccines based on specific keywords. In order to determine which keywords to include in the search, a manual inquiry was done on twitter where several Covid-19 related words were searched in order to see which rendered the greatest number of tweets. The tweets which include the chosen keywords will be recorded along with their location of origin. This data is currently being collected for all states. Once the collection is finalized, the data will then be processed through a sentiment analysis API in order to accurately indicate sentiment towards the Covid-19 vaccine in each tweet. This will then be used to visualize how each state generally feels towards the Covide-19 vaccine. This data may be able to provide insight to government officials on where to address and combat vaccine hesitancy.

Additional Abstract Information

Presenter: Stacy Fortes

Institution: Kean University

Type: Poster

Subject: Computer Science

Status: Approved

Time and Location

Session: Poster 5
Date/Time: Tue 12:30pm-1:30pm
Session Number: 4032