I have a chapter in Hemingway in the Digital Age: Reflections on Teaching, Reading, and Understanding (ed. Laura Godfrey, 2019, Kent State University Press): “How to Not Read Hemingway.” The chapter contains 20 different figures. Given the realities of publishing in academia, it was not possible to reproduce these figures in color. What’s more, some readers may benefit from being able to see larger versions of the images. For this reason, the press and I have agreed to publish the original images here.
Click on the image to see a larger version of it.
Fig. 1
The Prizmo interface.
Fig. 2
Voyant’s Summary tool for The Sun Also Rises.
Fig. 3
A word cloud of the most common terms in The Sun Also Rises, with stop words removed. In this visualization, I have used Voyant’s standard English stop-words list, plus the word said.
Fig. 4
Voyant’s Trend tool for The Sun Also Rises, which has been segmented into ten equal portions. The chart displays the raw frequencies (i.e., the total counts) for the terms brett, bull, cohn, jake, mike, and romero in each of those segments. Voyant ignores the case of the word when searching.
Fig. 5
The default view of Voyant—including the tools Cirrus, Reader, Trends, Summary, and Contexts—after loading the short stories and novels.
Fig. 6
Voyant’s Bubblelines tool displaying the terms fish*, water, camp*, and hunt* in the short stories and novels.
Fig. 7
Voyant’s Summary tool of the “all_fiction” and “all_nonfiction” corpora.
Fig. 8
Voyant’s Summary tool of the “all_living_fiction,” “all_living_nonfiction,” “all_posthumous_fiction,” and “all_posthumous_nonfiction” corpora.
Fig. 9
Voyant’s Trends tool displaying the relative frequency of said across the fiction corpus. This graph displays the relative frequencies (i.e., percentages). In other words, said makes up 1.5 percent of the words in The Complete Short Stories and 0.9 percent of the words in The Torrents of Spring. Note that the Trends tool employs “smoothing,” which accounts for the curves in the line that moves across the chart. Smoothing makes it easier for the human eye to see the patterns at play, but it is algorithmically determined. The only “real” data in this chart and the others from the Trends tool are the individual points.
Fig. 10
Voyant’s Trends tool displaying the relative frequency of said, thought, and think across the short stories and novels.
Fig. 11
Voyant’s Trends tool displaying the relative frequency of i and said across the short stories and novels. For this visualization, no stop words were used.
Fig. 12
Voyant’s Trends tool displaying the raw frequencies of scripps, yogi, and said across The Torrents of Spring, which has been broken into ten segments.
Fig. 13
Voyant’s Trends tool displaying the raw frequencies of said, brett, bill, mike, and cohn across The Sun Also Rises, which has been broken into ten segments.
Fig. 14
Voyant’s Trends tool displaying the raw frequencies of various character names across the “all_fiction” corpus, which has been broken into fifty-one segments.
Fig. 15
Voyant’s Trends tool displaying the relative frequencies of wine and beer across the short stories and novels.
Fig. 16
Voyant’s Trends tool displaying the relative frequencies of ate, drank, drink, and eat across the short stories and novels.
Fig. 17
Voyant’s Trends tool displaying the relative frequencies of afternoon, day, evening, morning, and night across the short stories and novels.
Fig. 18
Voyant’s Trends tool displaying the relative frequencies of boy, girl, man, and woman across the short stories and novels.
Fig. 19
Voyant’s Mandala tool displaying the short stories and novels, with the terms true*, truth, thought*, think*, knew, and know* acting as magnets.
Figure for footnote 14
Voyant’s Trends tool displaying the relative frequencies of the and said across the short stories and novels.
