Methods for Historical Text Data Collection: Introduction of the Everyday Life Method

Zachary D. Kline, University of Connecticut
Andrea Voyer, Stockholm University
Madison Danton, University of Connecticut

The proliferation of digital and digitized text data provides new opportunities and challenges for historical and cultural analyses. To date, historical computational sociology has predominantly relied upon two methods for selecting text: the Great Man Method, which ascribes significance to cultural texts surrounding specific events or those written by influential people, and the common-crawl method, which ascribes significance to random samples from large data gathered from as many widely-read sources as possible. This paper compares and contrasts these methods with our proposed alternative, the Everyday Life method, where data are theoretically selected based upon their significance to the culture of everyday life among a target population (Smith 1987; Goffman 1978). The Everyday Life method relies upon the assumption that reality is unfolding every day through lived experiences. Three data sets facilitate these comparisons: 1) presidential state of the unions; 2) Google-N Grams; 3) Emily Post’s etiquette manuals. Emily Post is explicitly charged with describing white middle-class social norms and thus, we argue, ideal for understanding everyday middle-class life. We use family as a heuristic to facilitate our comparisons and demonstrate how each of these methods of data selection provides a different picture of the associated sentimentality and cultural salience of single mothers over time. Smith, Dorathy E. 1987. The Everyday World as Problematic: A Feminist Sociology. Toronto: University of Toronto Press. Goffman, Erving. 1978. The Presentation of Self in Everyday Life. London: Harmondsworth.

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 Presented in Session 211. Theory and Methods in the Study of Culture