Some scholars think that ngrams and other data-​​mining approaches will win accep­tance when scholars make use, in a single paper, of both big data and tra­di­tional tex­tual analysis—which Aiden and Michel do not do. Ryan Cordell, an assis­tant pro­fessor of Eng­lish at North­eastern Uni­ver­sity, calls this “zoomable reading.” In a recent project for Dig­ital Human­i­ties Quarterly, he used text-​​mining of var­ious data­bases to iden­tify the 19th-​​century news­pa­pers that had reprinted a story by Nathaniel Hawthorne, “The Celes­tial Rail­road,” once con­sid­ered canon­ical but now all but for­gotten. He then showed why the story, involving notions of piety more con­ven­tional than the themes usu­ally asso­ci­ated with Hawthorne, would have appealed to readers, espe­cially reli­gious ones.


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