Inspiration
Twitter (or any other social media) may only make you easier see the comments from people with the same attitude. Covid-19 pandemic is a current topic.
What it does
Analyze the cases changes in recent days, the distribution of people's attitude toward COVID-19, and the relationship between them.
How we built it
Use Twitter api to get tweets from recent days about the same topic "covid-19"; Apply sentimental analysis on each tweet to get it's attitude; Get the proportion of people with positive, negative, and neutral attitude; Combine them with the daily cases data from the same days; Use linear regression to determine if there is a linear relationship between them.
Challenges we ran into
The use of API, process .json data. Process huge data set from WHO.
Accomplishments that we're proud of
Understand how API works and apply it in practical use; Use multiple graph type for different purposes; Build a relatively complex project by myself.
What we learned
How to use request, nltk... libraries properly; How to design a program; How to transform between different output type (json and csv).
What's next for Attitudes about COVID on Twitter and Daily New Cases
If possible, get an advanced Twitter Developer account to access more accurate analysis and filter.
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