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.