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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.