Machine Learning Methodologies and Large Data Text Corpora

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Abstract

With the rise of social media as a focal point for interaction in both global and local social communities, “big data” has become a key feature of social science research in the 21st century. As the size of corpora on sites like Facebook and Twitter have grown, a need has risen for more and more sophisticated computer science tools to collect data and both identify and visualize statistical trends therein. After describing our integration of Netvizz scraping software with our Statnews.org language analysis software we provide a case study of our tool’s application through analyzing Libertarian Facebook data, in particular a discussion about “milk rights” in the US, within the lens of Barnesmoore’s History of Assemblage Model (HoAM) and proceed (through use of thought experiment) to draw conclusions as to the ways in which the ontological regime(s) implicit in the analyzed data are likely to structure potential norms of thought, behavior, and being within publics socialized within the regime.