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Code for the data collection, cleaning and wrangling of U.S. presidential speeches, and the creation of predictive analysis models based on this data.

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conDavis/PresidentialPredictiveModel

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PresidentialPredictiveModel

Code Authored by: Eoin Daly, Constance Davis, Mara Hubelbank

The president of the United States is tasked with a number of near-impossible roles, one of which includes setting the national, and often global, agenda for his or her time in office. One of the means through which this is accomplished is via speeches to the American public. These speeches are scrupulously crafted and edited by the president's communications staff, with the final product ideally representing an encapsulation of the given executive branch's ideology and plans for action.

With this in mind, we set out to analyze patterns in presidential speeches, with a goal of understanding how their sentimentality and readability have changed over time. Using online-accessible speech corpora, we chose to look into trends of progressivist rhetoric within these speeches, focusing on the usage and importance of terms related to gender issues, equality, religion, and race; moreover, we put these features in the context of political party and time period, and look for correlations and predictability between these feature and target components. Moreover, we aim to analyze changes in presidential speech complexity by applying the Flesch-Kincaid readability tests to each president's corpus. Using our final output dataset, we aim to evaluate the extent to which we can predict the political party, time period, and speaker of a given speech based on the aforementioned attributes.

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Code for the data collection, cleaning and wrangling of U.S. presidential speeches, and the creation of predictive analysis models based on this data.

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