Distant Reading and Mapping Genre Space via Conjecture-based Distance Measures

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Distant Reading and
Mapping Genre Space via
Conjecture-based Distance
Measures
Juola, Patrick
juola@mathcs.duq.edu
Duquesne University
One of the key problems facing digital
humanities today is the increasing number
and size of digital repositories and the relative
lack of tools for studying them. A collection
of a million books (Crane, 2006) is no more
useful than a collection of ten thousand if
you can't read more than a hundred of them
in a realistic timeframe. Scholars like Moretti
(2005) have proposed a new analysis method,
termed "distant reading," to enable computer-
aided large-scale analysis of such collections.
In previous work (Juola and Bernola, 2009),
we have proposed using a conjecture generator
(Conjecturator, see also
http://www.twitter.c
om/conjecturator
) as another computer-aided
analysis method.
Underlying the Conjecturator is the idea that the
the computer can be deployed to autonomously
generate "facts" about a given text repository.
Like its predecessor and inspiration
Graffiti
(Fajtlowicz, 1988), the conjecturator generates
template-based "conjectures" that might or
might not be true about the repository and
the texts in it. A sample conjecture might be
something like:
-
The concept of "archivist" appears more in
mid-Victorian novels than in psychological
realism novels or, more obviously,
-
The concept of "femininity" appears more in
feminist novels than in novels with gothic
elements.
(Who would have thought, eh?)
As discussed in (Juola and Bernola, 2009), these
simple conjectures can be easily and quickly
tested to refute or confirm their validity. This
enables the computer to quickly generate a pile
of isolated "facts" about the text repository,
but does not provide a useful framework for
interpretation, explanation, or understanding
(which still requires human expertise).
However, this "pile of facts" can provide useful
source material for distant reading. In this
paper, we demonstrate one way to extend
this conjecture-based analysis to a large-scale
"distant reading" and visualization of genre
differences. Repeated generation of conjectures
will create a large catalogue of potential
differences between any particular category
pair, some true/supported, and some false. The
number of "true" differences, or alternatively,
the percentage of true differences, can be viewed
as a distance between the categories, a distance
measuring the degree of difference between
the concepts commonly written about in those
genres. If, for instance, "epistolary novels" differ
in 26 significant ways from "tragic novels", but
only in one significant way from "fiction of
manners," we can consider "epistolary novels" to
be a closer genre in terms of expressed concepts
to "fiction of manners" than to "tragic novels."
This high-order analysis gives us a large-scale
conceptual grouping of genre categories.
To aid in the study of such differences, we
compile the differences into a matrix and
apply multidimensional scaling (MDS) (Cox
and Cox, 2001). This statistical technique
takes a high-dimensional data set defined by
interpoint distances and embeds/rescales it to
fit a smaller number of dimensions (in this
case, two) while minimizing distortion. The
resulting two-dimensional coordinates can be
plotted to give a visual "map" of the space of
genres. We demonstrate this technique using
an enlarged set of 136 novels representing 36
genres (including time period and authorial
attributes as "genres") and approximately
10,000 validated conjectures (culled from
approximately 85,000 conjectures in total).
The resulting images clearly indicate that
this method is a new and viable way of
performing large-scale distant reading. As can
be seen in Figure 1, the resulting "map"
passes many obvious tests for rationality; for
for example, mid-Victorian novels represent
an intermediate stage between early and late
Victorian novels; similarly, "male authored
novels" in general are an intermediate between
"American male authored novels" and "English
male authored novels," reflected exactly what
intuition suggests. We leave it to genre

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specialists to examine the map in detail and to
see whether actual genres equally reflect our
intuitions. It is easy and relatively efficient to
apply and almost entirely document-agnostic; it
can be applied as easily to journal articles (and
map the space of scholarship) or to newspaper
corpora (perhaps mapping the space of editorial
policies and politics) as to novel genres.
Figure 1
References
Cox, T.F., Cox, M.A.A.
(2001).
Multidimensional Scaling.
Chapman and Hall.
Crane, Gregory
(2006). 'What Do You Do
With a Million Books?'.
D-Lib Magazine.
12(3)
.
Fajtlowicz, Siemion
(1988). 'On conjectures
of Graffiti'.
Discrete Mathematics.
72
.
Juola, Patrick
(2009). 'Mapping Genre
Space via Random Conjectures'.
Presented at
DHCS-2009, IIT.
Chicago, IL.
Juola, Patrick, Bernola, Ashley
(2009).
'Conjecture Generation in the Digital
Humanities'.
Proc. DH-2009.
2009.
Moretti, Franco
(2005).
Graphs, Maps,
Trees: Abstract Models for a Literary History.
Verso.