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README.md

SlidesPDXDataScienceApril2016

Slides presented at PDXData Science R User Group with the associated Meetup Page

Apr 5, 2016 NLP meets Politics-Experiment­s w/ Word-Vectors and 2016 Campaign Debate Rhetoric

Speaker: Winston Saunders

Abstract: Word vectors, derived by deep learning algorithms applied to billions of words of text, provide powerful semantic models of language. Code in R, demonstrating [queen] + [man] - [woman] ~ [King] to about 90% accuracy will be reviewed. Building first on exploratory “bag of words” analysis of Presidential debate texts, we’ll explore, using pre-computed GloVe vectors (Pennington et al http://nlp.stanford.edu/projects/glove/), relationships like [sanders] + [trump] - [clinton] ~ [cruz] and how candidate positions align to rhetorical sentiment like [government] + [people] - [tax]. This analysis is work in progress. We’ll also test empirical limits (aka failed experiments). Active feedback is both sought and welcome

####FILES: Politics Meets Word Vectors in R.pdf: a pdf version of the slides

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