Background

COVID 19 disease has been crippling the world since 2019, bringing the world to a standstill, crashing global economies, families stranded and unable to meet during holidays, occasions, students attending schools and universities virtually for the last two years. Besides that, around the world 5 million have died due to this deadly disease and in the USA alone around 804,758 have died due to COVID-19. So far there has been no sign of the pandemic truly ending and we are completely going back to our “normal lives”, the only respite we have had so far is the introduction of COVID-19 vaccination. Though introduction of the vaccine has proven itself to be the best way to limit the spread of the supplemented by social distancing and wearing facemask in public spaces, being fully vaccinated doesn’t mean you will 100% contract the virus, you might still fall sick due to COVID-19 but it wouldn’t be as severe and life threatening if not fully or not vaccinated at all. To say the least the introduction of the vaccine has not been necessarily positive across the world for multiple reasons. This coupled with people’s apprehension on how fast the vaccine was developed and released for public usage has not instilled much confidence either. In current day with expansive reach of the internet, there surely has been a lot of mis-information or myths about the vaccine like

“A COVID-19 vaccine can make me sick with COVID-19.”

“COVID-19 vaccines contain microchips.”

“The natural immunity I get from being sick with COVID-19 is better than the immunity I get from COVID-19 vaccination.”

“COVID-19 vaccines authorized for use in the United States shed or release their components.”

These being a few them, we are here analysis tweets on twitter to understand people sentiments and emotional reaction to COVID-19 vaccine. It’s important for governments to understand the potential drivers that affect public’s attitudes towards COVID-19 vaccines based on social media, which generates abundant user-based data. We will be focusing our study in USA, which we believe in correlation with stats on fully vaccinated people around all the USA states would be rather helpful for health professionals and policy makers to understand the sentimental awareness of states that are lacking or not as highly vaccinated as other states.

Generally, this project would be devided into 4 parts:

• Sentiment and emotional analysis,
• Keyword modeling and cloud mapping
• Predict the sentiment from tweets with machine learning
• Spatial analysis of the tweets - positive and negative

For detailed codes about this project, please click here.