Tracking the public opinion of the 2020 US Presidential Election candidates
I just wanted to get some hands on expirience on working with a ML project This project involves webscraping using Twitter's API and sentiment analysis using TextBlob
It searches for tweets related to presidential election candidates, the tweets are identified using hashtags for example'#sanders2020'. The tweets along with some metadata are stored in csv files
Pandas is then used to analyse the data, the polarity of the sentiment of the tweet is identified using TextBlob and stored back in the csv files, the pandas aggregation funtions are used to get some statistical measures
The front end was built using materialze.css , a powerful framework like that and a coder without an ounce of artistic creativity dont mix well, so the front end design is so and so , but they fullfill their purpose
1)The backend is built using Python3 and runs on a Flask server
2)The front end is built using HTML5 and materialze.css
I might add some graphs , why? because graphs look cool, when? in near future, if i get bored