Summary of Words Of War: Exploring the Presidential Rhetorical Arsenal with Deep Learning, by Wyatt Scott et al.
Words of War: Exploring the Presidential Rhetorical Arsenal with Deep Learning
by Wyatt Scott, Brett Genz, Sarah Elmasry, Sodiq Adewole
First submitted to arxiv on: 12 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper applies deep learning techniques to analyze the nuances and patterns in US presidential speeches preceding major conflicts. The goal is to identify subtle features that signal US involvement in wars, going beyond accurate classification to interpretable learning. By examining presidential rhetoric, the project aims to uncover underlying dynamics of decision-making at the highest level of governance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In this study, researchers use deep learning methods to analyze US presidential speeches before major conflicts. They want to find hidden patterns and clues that can predict when the US will get involved in a war. Instead of just being able to correctly classify whether a speech is about war or not, they’re trying to figure out what specific words or phrases are most important for understanding the president’s intentions. |
Keywords
» Artificial intelligence » Classification » Deep learning
