Election Twiter Sentiment Analysis

This repo contains the code for the web app created to analyze real-time tweet sentiments that are posted about democractic candidates.

Ideas

There are a few ideas that i need to consider. For instance,

The number of positive and negative tweets posted for each candidate
The proportion of positivity and negativity
How these change over time and possibly after each debate or major event
Is there any relationship between the tweets sentiments and the pols?
The location of the sentiments, broken down to the states, possibly focusing on the swing states.
We can expand the analysis beyond the tweets and to the users/voters.
Make a word cloud for the tweets about each candidate?

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
__pycache__		__pycache__
static/js		static/js
templates		templates
venv		venv
.gitignore		.gitignore
app.py		app.py
clean_tweet.py		clean_tweet.py
contractions.py		contractions.py
election.sqlite		election.sqlite
expand_contractions.py		expand_contractions.py
expand_hashtags.py		expand_hashtags.py
readme.md		readme.md
remove_mentions.py		remove_mentions.py
requirements.txt		requirements.txt
sentence.py		sentence.py
sentiment.py		sentiment.py
sqlalchemy_declarative.py		sqlalchemy_declarative.py
stream.py		stream.py
tweet.py		tweet.py
tweet_downloader.py		tweet_downloader.py
tweet_streamer.py		tweet_streamer.py
var.py		var.py