The aim of this work is to understand how frequency and sentiment of Covid-19 vaccines' nomenclatures changed over time. The manufacturing of vaccines plays an important role for Covid-19 pandemic to be contained. There are currently about half a dozen leading vaccine manufacturers in late-stage trials, according to the World Health Organization (WHO), including three in China, one in the UK, one in the US, and a German-US partnership. We would like to investigate:
1-) How the nomenclature of vaccines differs in Turkey and how it is reflected on the attitude toward vaccination
2-) Whether any of these vaccines are promoted or demoted by the international media sources that are active in Turkey by looking at the sentiments and frequencies of Covid-19 related vaccine news.
3-) Whether pronoun usage differs according to the sentiment of tweets.
4-) If there is any observable effect of the number of bots on social perception toward vaccination.
Installation
We used Google Colaboratory, Python 3.9.5- Jupyter, and R, R Studio for the study. Python --> https://www.python.org/downloads/release/python-395/ R --> https://cran.r-project.org/bin/windows/base/
Data Collection
We used Twitter's academic API to obtain the dataset that contains some keywords. The time interval of the tweets is determined as from March 1, 2020 to June 18, 2021. Key words: ("çin aşı", "cin asi", "sinovac", "biontech", "pfizer", "alman asi", "alman aşı", "rus asi", "rus aşı", "sputnik asi", "sputnik aşı", "sputnik ol", "germen asi", "germen aşı", "gavur asi", "gavur aşı", "korona aşı", "covid aşı", "korona asi", "covid asi", "kovid asi", "kovid aşı", "mrna", "coronavac","biontek","biyontek","bayontek","biyonteck", "sinowac","sınovac","koronavac","koronavak","sinovak","fayzır","fayzir","pifizer","fizer","sputnikv","sputnik bes","sputnik 5")