The new methods of “big data” analysis can inform and expand historical analysis in ways that allow historians to redefine expectations regarding the nature of evidence, the stages of analysis, and the claims of interpretation.1 For historians accustomed to interpreting the multiple causes of events within a narrative context, exploring the complicated meaning of polyvalent texts, and assessing the extent to which selected evidence is representative of broader trends, the shift toward data mining (specifically text mining) requires a willingness to think in terms of correlations between actions, accept the “messiness” of large amounts of data, and recognize the value of identifying broad patterns in the flow of information.2
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