Username: dtradke, CCV
This repository works towards question #9 on the webpage https://www.notion.so/Analytics-Bounties-for-Compound-62013e59c5d04b4281d0868efdcfaab0. This question revolves around analyzing Twitter data's impact on the Compound (COMP) cryptocurrency using Flipside Crypto data. We use data analytics and natural language processing and data analytics to summarize how overall tweet volume, mean tweet sentiment, and tweet reach impact the price of COMP.
Our solution is located in a jupyter notebook. The notebook can run off of offline saved data to curcumvent the necessity for a Twitter Developer account. If you have an account, the notebook can use real-time data to update the attached graphs.
We have included multiple ways to view the report:
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COMP_3rd_Party.ipynb --> This is a jupyter notebook. The code can be actually run in here by execting "jupyter notebook COMP_3rd_Party.ipynb" in terminal from this directory.
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COMP_3rd_Party.pdf --> This is an exported PDF document of the write-up and code included in the jupyter notebook. This also includes the graphs that the code generates.