Close readings of big data: Triangulating patterns of textual reappearance and attribution in the Caledonian Mercury, 1820-1840

This essay demonstrates how the iterative use of close and distant reading with historical newspapers can provide new and complementary evidence of the role of scissors-and-paste journalism, or reprinting, in the spread of news content. Using Gale's nineteenth-century British newspaper collections, this paper suggests how best to read the evidence of duplicated content obtained through text mining and explores the extent to which this level of analysis can distinguish between different editorial or production styles. Delving into a close reading of the Caledonian Mercury between 1820 and 1840, this study then tests hypotheses about word count and publication frequency developed through distant reading and determines its most common editorial structures. The study concludes with an exploration of how to extrapolate conclusions from close readings to support a more nuanced understanding of the results of large-scale textual analyses. Overall, it argues that iterative testing through both big data and close reading methodologies, a so-called middle-scale analysis, provides a better method for understanding the ambiguous and shifting structures of nineteenth-century newspapers as well as the points of connection between them