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      Toward a computational hermeneutics

      1 , 2 , 3 , 1 , 2 , 3 , 1 , 2 , 3
      Big Data & Society
      SAGE Publications

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          Abstract

          We describe some of the ways that the field of content analysis is being transformed in an Era of Big Data. We argue that content analysis, from its beginning, has been concerned with extracting the main meanings of a text and mapping those meanings onto the space of a textual corpus. In contrast, we suggest that the emergence of new styles of text mining tools is creating an opportunity to develop a different kind of content analysis that we describe as a computational hermeneutics. Here the goal is to go beyond a mapping of the main meaning of a text to mimic the kinds of questions and concerns that have traditionally been the focus of a hermeneutically grounded close reading, a reading that focuses on what Kenneth Burke described as the poetic meanings of a text. We illustrate this approach by referring to our own work concerning the rhetorical character of US National Security Strategy documents.

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          Most cited references40

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          Social science. Computational social science.

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            Quantitative analysis of culture using millions of digitized books.

            We constructed a corpus of digitized texts containing about 4% of all books ever printed. Analysis of this corpus enables us to investigate cultural trends quantitatively. We survey the vast terrain of 'culturomics,' focusing on linguistic and cultural phenomena that were reflected in the English language between 1800 and 2000. We show how this approach can provide insights about fields as diverse as lexicography, the evolution of grammar, collective memory, the adoption of technology, the pursuit of fame, censorship, and historical epidemiology. Culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities.
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              Measuring Resemblance in Sequence Data: An Optimal Matching Analysis of Musicians' Careers

                Author and article information

                Journal
                Big Data & Society
                Big Data & Society
                SAGE Publications
                2053-9517
                2053-9517
                December 01 2015
                December 01 2015
                December 01 2015
                : 2
                : 2
                : 205395171561380
                Affiliations
                [1 ]University of California, Santa Barbara, CA, USA
                [2 ]The New School, New York, NY, USA
                [3 ]University of Arizona, Tucson, AZ, USA
                Article
                10.1177/2053951715613809
                b8ca8b1a-a5c9-43d8-8bc1-98e51ff79b08
                © 2015

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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