Inspiration: We were inspired by Elon Musk and his ability to influence the market of cryptocurrencies simply by tweeting.

What it does: The project analyzes tweets of Elon Musk that contain keywords relating to cryptocurrencies and DogeCoin, we chose DogeCoin to specifically determine the correlation between his tweets and the price.

How we built it: We built the front end using HTML and CSS, then using Apify to convert the information inside of Elon Musk's tweets into a .json file. Using the .json file we were able to analyze them in a python script, where we manually took our findings and put them on the front-end.

Challenges we ran into: Being able to extract the information from the tweets was difficult because we couldn't find an API and traditional web scraping would not work with Twitter. We eventually came across Apify, which made our lives easier. Also, the graph was quite hard to make, we used Matplotlib, to make it and we had to convert the dates to integers onto the x-axis.

Accomplishments that we're proud of: Using Object-oriented programming to create ElonMuskTweet objects which we used to store all of the attributes of each tweet, made analyzing large amounts of data easier.

What we learned: How to use Object-oriented programming to analyze large amounts of data and using API's

What's next for Elon Musk Twitter Tracker: We want to make it be able to live update with more recent tweets, as well as make the front-end more interactive.

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