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  1. Toward a computational hermeneutics.Ronald L. Breiger, Robin Wagner-Pacifici & John W. Mohr - 2015 - Big Data and Society 2 (2).
    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 (...)
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  • Humanistic interpretation and machine learning.Juho Pääkkönen & Petri Ylikoski - 2021 - Synthese 199:1461–1497.
    This paper investigates how unsupervised machine learning methods might make hermeneutic interpretive text analysis more objective in the social sciences. Through a close examination of the uses of topic modeling—a popular unsupervised approach in the social sciences—it argues that the primary way in which unsupervised learning supports interpretation is by allowing interpreters to discover unanticipated information in larger and more diverse corpora and by improving the transparency of the interpretive process. This view highlights that unsupervised modeling does not eliminate the (...)
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