Background: Announcements of mRNA vaccines rollouts were aggressively promoted from August 2020 onwards till now (August 2021). In the process, there were rampant cases of misinformation published on social media. This obstacle had significantly hindered the countries' progress to get all their citizens vaccinated as soon as possible to avoid a crisis whereby their healthcare systems would be massively overutilised to the extent that they cannot provide adequate care to everyone who needs it.
As an attempt to tackle the spread of misinformation on social media, misinformation had to be detected early so that people were not misled into believing that the mRNA vaccines were harmful and subsequently, encourage them to take the vaccines to protect themselves.
This is an illustration of how I used Python to extract tweets containing the terms "mRNA vaccines" so that these tweets could be picked up by the operations team for moderation purposes and analysed by the data team to have insights into how misinformation spreads and how much influence it has on the viewers.
Data was sorted according to number of retweets and likes respectively, in a descending order. Final data was exported via csv format.