Democrat Vs. Republican Tweets

Context

Twitter give the general public unfiltered direct access to the ideas and policies of politicians. This means that understanding the content and reach of these tweets can help us understand what connects with constituents. This dataset is meant to help with that exploration. By applying sentiment analysis (using an already trained system) we can apply sentiment context to these tweets. This will help us understand who responds to positive and negative content. Finally this analysis may help to indentify fake or hyperbole polarized Twitter users.

Content

The dataset contains two files both in .csv format. The first is a list of the political party and the representative handles, and the second are the 200 latest tweets as of May 2018 from those twitter users.

Acknowledgements

I would like to thank the following website and people who helped me get started

Inspiration

I was first inspired by trying to find out if the average person would be able to distinguish between political tweets of no context was given. I made a small website that you can try this on. I will use real user data to cross check and see if ML methods are actually better than the average person.

Other ace uses are the following:
Can we use this to detect Russian troll twitter accounts?
Do people respond to negative or positive political tweets?