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What happens if we use natural language processing to analyze every presidential State of the Union speech in US history?

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State-of-the-Union

This is a project I worked on during Spring 2019. 2019's SOTU was particularly controversial due to the US government shutdown from December 2018 to January 2019. As a result, the speech was postponed to February. In light of the speech being in the national spotlight, I was inspired to research the history of the speech and analyze the speech text for trends in topics over time.

If you want to view the Jupyter Notebooks I've created without downloading the files, check out the following links:

  1. Text Analysis Demo: https://nbviewer.jupyter.org/github/ritvik-iyer/State-of-the-Union/blob/master/DIP%20Presentation%20Modeling%20DEMO.ipynb

  2. Project Report: https://nbviewer.jupyter.org/github/ritvik-iyer/State-of-the-Union/blob/master/State%20of%20the%20Union%20Analysis-%20Final%20Write%20Up.ipynb

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What happens if we use natural language processing to analyze every presidential State of the Union speech in US history?

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