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Political Semantics: Methods and Applications in the Study of Meaning for Political Science

Posted by on Thursday, January 16, 2020 in Uncategorized.

February 28, 2020 | 12pm
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Political Semantics: Methods and Applications in the Study of Meaning for Political Science

The past few years have seen enormous advances in the computational modeling of language. These innovations offer social scientists the potential to move beyond the use of linguistic data for descriptive analyses —a valuable endeavor in and of itself— to quantitative models that allow us to identify latent patterns in language usage. My research advances these techniques to study group differences in how “meaning” is represented in memory and implications for the study of (political) attitudes. In this seminar I will touch upon a series of ongoing multi-disciplinary projects introducing novel methods for the study of meaning and representational differences leveraging various types of data including, crowdsourced word-associations, large collections of text and brain imaging (fMRI).

About Pedro

Pedro L. Rodríguez is a Ph.D. graduate from NYU’s Wilf Department of Politics and current Postdoctoral Fellow at Vanderbilt’s Data Science Institute. Pedro’s primary research explores partisan differences in the representation of language in memory. Building on the premise that patterns in natural language are informative of the content and organization of memory—the pictures in our heads—in his dissertation he developed methods to study the semantic representations of politically charged concepts (e.g. welfare, abortion, justice) and evaluate their role in attitude judgments. His research draws from multiple disciplines including cognitive science, computer science, linguistics and social psychology. Pedro is also broadly interested in the application of computational methods to the social sciences, with emphasis on networks, NLP and machine learning.