Started as a CS project in our HS. Maintaining this even after our class has ended.

What it does

We will be getting user timeline information from the Twitter API and use it to find trending words within a user's Twittersphere with its appropriate sentiment score

This app will give you the trending entities in a given Twitter Timeline with a ranked list of the most Postive and most Negative keywords.

How we built it

The code's architecture will be fairly simple. We'll have a back-end script that will take the user input Twitter handle and submit a request to Twitter for the information. Once we get that information, we will do the data parsing on that same script. The most basic output of this script will be a dictionary containing the most popular entities with their sentiment score.

In addition, we used to APIs, Alchemy and Twitter.

Challenges I ran into

Accomplishments that I'm proud of

What I learned

Python How to attempt to plan for a project

What's next for Tweetalyzer

Move all the files to Git and use Heroku to host

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