=Paper= {{Paper |id=Vol-3290/long_paper1576 |storemode=property |title=A Quantitative Study of Fictional Things |pdfUrl=https://ceur-ws.org/Vol-3290/long_paper1576.pdf |volume=Vol-3290 |authors=Andrew Piper,Sunyam Bagga |dblpUrl=https://dblp.org/rec/conf/chr/PiperB22 }} ==A Quantitative Study of Fictional Things== https://ceur-ws.org/Vol-3290/long_paper1576.pdf
A Quantitative Study of Fictional Things
Andrew Piper, Sunyam Bagga
McGill University, 680 Sherbrooke St., Montreal, QC H3A 2M7, Canada


                                      Abstract
                                      In this paper, we apply machine learning based predictive models on two large data sets of historical and
                                      contemporary 昀椀ction to better understand the role that things play in 昀椀ctional writing. A large body
                                      of scholarship known as “thing theory” has attempted to understand the function of 昀椀ctional things
                                      within literature mostly by focusing on small case studies. We provide the 昀椀rst-ever estimates of the
                                      distribution of di昀昀erent types of things in English-language 昀椀ction over the past two centuries along
                                      with experiments to model their semantic identity. Our 昀椀ndings suggest that the most common 昀椀ctional
                                      things are structural in nature, functioning akin to narrative props. We conclude by showing how these
                                      昀椀ndings pose problems for inherited theories of 昀椀ctional things and propose an alternative theoretical
                                      framework, embodied cognition, as a way of understanding the predominance of structural things.

                                      Keywords
                                      thing theory, embodied cognition, 昀椀ction, narratology, machine learning, natural language processing




1. Introduction
Over the past two decades, a large body of research has emerged in the 昀椀eld of literary studies
focusing on the question of “things.” “Thing theory,” as this area has come to be known [8],
has its origins in di昀昀erent research traditions, including the rise of material cultural studies
[1], new historicism [18], and media theory [21, 33, 27]. At the heart of this work has been an
attempt to move attention away from the symbolic aspects of o昀琀en natural objects in litera-
ture – an interpretive tradition grounded in European Romanticism – towards the materiality,
physicality, and the madeness of 昀椀ctional things. In doing so, thing theory reorients critical
attention around di昀昀erent kinds of things and di昀昀erent kinds of roles that things may play in
the history of imaginative literature.
   In this paper, we apply machine learning based predictive models on two large data sets of
historical and contemporary 昀椀ction to better understand the role that things play in 昀椀ctional
writing. We de昀椀ne things for our purposes as any non-human object and thus distinguish them
from people, places, or human body parts like faces and eyes. Our aim is to better understand
the function that imaginary objects play in the practice of creative storytelling and how this
has potentially changed over time. Despite a wealth of recent case studies that focus on par-
ticular types of things in individual books [17, 31, 20, 22, 32], only one work to date has used
computational methods to study the broader distribution of 昀椀ctional objects [28]. If we want
to understand what Brown has called “a genuine sense of the things that comprise the stage

CHR 2022: Computational Humanities Research Conference, December 12 – 14, 2022, Antwerp, Belgium
£ andrew.piper@mcgill.ca (A. Piper); sunyam.bagga@mail.mcgill.ca (S. Bagga)
ȉ 0000-0001-9663-5999 (A. Piper)
                                    © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
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 Workshop
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               http://ceur-ws.org
               ISSN 1613-0073
                                    CEUR Workshop Proceedings (CEUR-WS.org)




                                                                                                     268
on which human action, including the action of thought, unfolds” (5) [11], then it is impera-
tive that we develop methods that can more su昀케ciently account for the broader population of
things in creative writing.
   Accordingly, we have two primary aims in this paper. First, we provide the 昀椀rst-ever esti-
mates of the distribution of things in 昀椀ctional writing over the past two centuries. For the 昀椀rst
time, we can observe the kinds of things that populate 昀椀ctional writing at least with respect
to a single major language. Second, we conduct a series of experiments to better describe the
semantic identities of things as a way of inferring their narrative function. Doing so can help
us engage with longstanding debates about the nature and role of 昀椀ctional objects within the
昀椀eld of thing theory.
   Based on the data we provide here, we 昀椀nd that the most predominant type of 昀椀ctional things
since the nineteenth century are “infrastructural” in nature. By infrastructural we mean three
key qualities: the 昀椀rst, ontological in nature, is that the most common types of things in 昀椀ction
are more likely to be structural rather than, say, instrumental or vehicular or organic. The most
prevalent things in 昀椀ction hold other things up. They provide narrative support. Thus for us
infrastructure does not more narrowly refer to the contemporary usage of “airports,” “roads,”
etc., but rather to human-made structures more generally, such as rooms, doors, tables, walls,
and homes that help support other objects.
   The second way we mean infrastructural is that these things are also distinctively semanti-
cally inert: as we will show through di昀昀erent experiments, structural things are less descrip-
tively rich than other kinds of entities, less a昀昀ectively charged, and more associated with phys-
ical rather than cognitive or emotional behavior. Such things are more semantically inert than
other kinds of entities. They appear to function more as vehicles of embodiment than intellec-
tion. Third and 昀椀nally, we mean infrastructural in the sense that such structural things appear
regularly throughout narrative time. They are consistently woven throughout the whole nar-
rative rather than functioning as singularly important entities. Their continued prevalence is
a key part of their meaning.
   Overall, then, the most predominant things in 昀椀ction appear to function as “props” in mul-
tiple senses of the word: they physically hold other things up; are descriptively shallow; and
predominate throughout narrative space and time. As we discuss at the close of our paper,
we think these insights have important implications in modifying the inherited views of thing
theory and the role that 昀椀ctional things play in literature.


2. Data
The primary datasets we use for this paper are, 昀椀rst, the Hathi1M dataset which consists of
1,671,370 randomly drawn pages from over 300,000 volumes of English prose in the Hathi Trust
digital library [3]. These volumes span the years 1800-2000 and consist of an approximate bal-
ance of pages labeled as 昀椀ction and non-昀椀ction. The second, the CONLIT dataset [25], is a
collection of 1,934 works of English-language 昀椀ction drawn from eight di昀昀erent genres pub-
lished between 2001 and 2021 largely North American in origin. Books in the contemporary
collection were manually curated to represent popular writing aimed at reaching di昀昀erent read-
erships (i.e. “genres”). While the term “genre” has been understood in multiple ways within




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Table 1
The five most common super-sense tags and most-frequent associated words
                    Noun Type                 Examples            Verb Type        Examples
                     person           man,mother,father            stative         was,is,be
                     artifact          door,room,house          communication      said,say,told
                 communication        name,words,word              motion          go,came,come
                    location            place,side,city            contact         put,stood,sat
                      body              eyes,head,face            cognition        know,think,knew


Table 2
Primary super-sense tags used to represent things in this paper
                                   Thing            Examples         Category
                                   artifact      door,room,house     human-made
                                    object      world,ground,sky     organic
                                   animal       horse,dog,animals    organic
                                     food       food,co昀昀ee,dinner   organic
                                    plant         trees,tree,grass   organic


the research community [16, 30], we de昀椀ne genre for our purposes as a form of institutionally
framed classi昀椀cation [19], where we use three broad categories of framing: cultural capital
(bestsellers, prizewinners, elite book reviews), stylistic a昀케nity (mysteries, science 昀椀ction, ro-
mance, etc.), and age-level (middle-grade and YA).
   In order to detect entity-types in our data, we process all texts using bookNLP [4], which
implements BERT-based models and has been shown to outperform other state-of-the-art sys-
tems for a variety of NLP tasks when applied to literary texts [5]. In addition to performing
entity recognition, part-of-speech-tagging, and dependency parsing, bookNLP also provides 41
“super-sense” tags trained on SemCor’s implementation of the Wordnet taxonomy, examples of
which are shown in Table 1. In Table 2, we provide a list of noun-types that we use to capture
two categories of things as either human-made or organic. According to bookNLP’s documen-
tation, the supersense tagging has an accuracy of 76% when applied to works of 昀椀ction.
   Prior work on the computational detection of objects in 昀椀ction has applied a dictionary-
matching approach using the Wordnet taxonomy to a small set of sixty nineteenth-century
novels [28]. Our work updates this work by a) examining a considerably larger collection
of 昀椀ction and b) using predictive modeling for word-type tagging. Problems of word disam-
biguation surrounding dictionary-matching methods are well known [24], which may prove
especially problematic in 昀椀ction when, for example, highly prevalent character names (such
as “Iris,” “Ivy” etc.) can be confused for objects when taken out of context. Additionally, in
contrast to Tenen [28] who only counts entities that appear as grammatical objects, we condi-
tion on all appearances of nouns given that objects can play an important role as the subject of
actions. Our results thus depend on the predictions made by bookNLP’s super-sense tags for
all nouns in a given book.1
1
    All data and code can be found in the following repository: https://doi.org/10.6084/m9.昀椀gshare.21382020.v1




                                                          270
3. Results
3.1. The prevalence of things
Fig. 1 provides an overview of the distribution of noun-types across three historical periods.
As we can see, humans dominate 昀椀ctional narrative regardless of historical time-frame. Never-
theless, human-made things (“artifacts”) are second, a surprising result given no prior theory
has indicated this kind of predominance. Indeed, we 昀椀nd that the rate of artifacts across all
three collections is 2.4x higher than all other natural objects combined and 3.3x higher if we
condition on the contemporary data. As Fig. 1 indicates, the prevalence of artifacts increases
from the nineteenth-century to the present (note the reversed order of persons and artifacts by
period).
   We can also observe that this increase of artifacts over time is speci昀椀c to 昀椀ction (Fig. 2).
Despite the simultaneous growth of artifacts in 昀椀ction and non-昀椀ction over the course of the
nineteenth century, by the early twentieth century we see 昀椀ction investing more heavily in
the utilization of human-made things. By the end of the twentieth century, artifacts in 昀椀ction
are almost 50% more frequent than in non-昀椀ction, averaging roughly 3 more occurrences per
page than an equivalent work of non-昀椀ction. Artifacts also represent the semantic category
with the single strongest growth over this time period. Human-made things come to dominate
昀椀ction beyond what we expect from their overall prevalence in English-language writing more
generally.

3.2. The nature of things
To better understand the nature of human-made things and their distribution in 昀椀ction, we
break down the artifact category by various sub-types. To do so, we use Wordnet’s hypernym
taxonomy. For each word predicted to be an artifact in our dataset, we crawl the hypernym tree
for the word’s most common sense and store all types that occur below the level of “artifact.”
For example, the word “house” would produce the following sub-types in the following order
of ascending generality: dwelling, housing, structure. We condition on 2,500 / 1,800 of the most
common artifacts in the contemporary / Hathi collection, which account for just under 80% /
90% of all occurrences of artifacts in each collection. We then manually review and clean the
labels, producing the following sub-types and their counts in Table 3.
   As we can see, “structures” are the most common kind of object in 昀椀ction by a factor of 1.5
over the next most frequent type, human-made instruments. Indeed, the frequency of struc-
tures is higher than all of the organic objects combined. This holds for the Hathi1M collection
with the exception that there are considerably more natural objects utilized in the nineteenth-
and twentieth-century data. Beyond this divergence, the ranking and even the top words of the
various categories are remarkably similar (full data provided in the supplementary material).

3.3. Semantic frameworks of things
With a clearer picture of the distribution of the types of 昀椀ctional things, we take the next step
of trying to better understand the semantic identity of these things, and structural things in
particular. Knowing that human-made things dominate 昀椀ction in terms of object types and




                                               271
Figure 1: Distribution of entity-types by historical period


knowing that within that group structures are the most common sub-type can give us impor-
tant information about the potential narrative function of 昀椀ctional things. Here we wish to
deepen our understanding by undertaking a series of tests to gain further insights about the
semantic frameworks that surround structural things. We note that when we refer to “struc-
tures” in this section we combine words labeled as “structures” and “furnishings” because we
consider tables, chairs, etc to also function as structural forms for our purposes.

3.3.1. Modification
Wall [31] has argued that by the nineteenth century 昀椀ctional things assume a more ornamen-
tal or decorative function, that is, they move from being inert, non-descript objects like “the
pot” famously identi昀椀ed by Virginia Woolf in her essay on Robinson Crusoe [34] to serving as
elaborate descriptive props for writers like Balzac, Flaubert, and Dickens. In order to test this
theory, we measure the ratio of the rate of the modi昀椀cation of artifacts divided by the rate of
modi昀椀cation of other kinds of entities. Doing so allows us to understand how much more likely
artifacts are to be modi昀椀ed given the overall rate of modi昀椀cation per book / year, which we
assume varies from book to book and from year to year. To detect whether an entity has been
modi昀椀ed, we condition on the following three forms of grammatical modi昀椀cation: adjectival
modi昀椀ers, participial modi昀椀ers, and clausal modi昀椀ers, which are represented by the Stanford




                                                 272
Figure 2: Distribution of artifacts over historical time in fiction and non-fiction


Dependency Parser as “amod,” “partmod,” and “rcmod” respectively. We show examples of
each form in Table 4 and the results of our comparisons in Table 5.

3.3.2. A昀昀ect
In addition to description, we also measure the rate of “a昀昀ect” associated with di昀昀erent kinds
of 昀椀ctional things. Research has emphasized the ways in which objects in 昀椀ction are o昀琀en
embedded in psychically or emotionally charged contexts [12]. In order to measure relative
levels of a昀昀ect surrounding artifacts, structures, and other kinds of entities, we use the NRC
valence-arousal-dominance lexicon [23] and calculate the average valence and arousal for a
random sample of sentences drawn from each book / year. We then subset our samples by
whether they contain artifacts and structures and compare the distributions of those values for
each historical period. We use Cohen’s d as a measure of e昀昀ect size when comparing categories.
   As we can see in Table 5, when it comes to modi昀椀cation we see a small increased rate of
modi昀椀cation of artifacts when compared to other kinds of entities, which shi昀琀s in the oppo-
site direction when we condition only on structures and furnishings. Structures are unique
in their lower levels of description. For a昀昀ect, we see a small negative relationship between
artifacts and their valence scores for the historical data and a large negative relationship for the
contemporary collection, which grows stronger as we move from all artifacts to our subset of




                                                  273
Table 3
List of sub-types and counts in the contemporary collection with the most frequent words for each
type.
              Category             Type          Count (per 100K)   Examples
               artifact          structure             874          door,room,house
               artifact      instrumentality           557          phone,gun,bag
               artifact          clothing              277          clothes,shirt,pocket
               organic             object              254          world,ground,sky
               organic              food               225          food,co昀昀ee,dinner
               organic            animal               197          horse,dog,animals
               artifact         furnishing             149          bed,table,chair
               artifact           vehicle              135          car,ship,truck
               organic             plant               102          trees,tree,grass
               artifact          creation              63           picture,pictures,photo
               artifact              line               9           rope,string,napkin
               artifact         plaything               5           cards,doll,toy


Table 4
Examples of our three types of modification. Entities are underlined and modifiers appear in italics
       amod               partmod                               rcmod
       broad streets      the net became cracked                the tube that surrounded it
       short sleeves      a hook measuring about two inches     the co昀昀in which sat on the table


Table 5
Rates of modification and valence scores associated with di昀昀erent kinds of entities for each period.
Cohen’s d represents the e昀昀ect size when comparing the distributions of rates associated with a given
type and all other entity types (e.g. artifacts v. non-artifacts).
                          Period      Type         Measure              d
                           19C       Artifacts   Modification   0.001 (negligible)
                           20C       Artifacts   Modification      0.36 (small)
                           21C       Artifacts   Modification      0.33 (small)
                           19C       Artifacts     A昀昀ect          -0.29 (small)
                           20C       Artifacts     A昀昀ect          -0.36 (small)
                           21C       Artifacts     A昀昀ect          -1.57 (large)
                           21C      Structures   Modification      -0.13 (small)
                           21C      Structures     A昀昀ect          -1.79 (large)


structures. This suggests that structures are functioning less ornamentally and less a昀昀ectively
than other kinds of 昀椀ctional entities.




                                                    274
3.3.3. Narrative Distribution
Another way to understand the meaning of objects in 昀椀ction is to observe their distribution
across narrative time [10]. Fictional things may play a strategic role by occurring at key turning
points or narrative entry or exit points or conversely they may play a more infrastructural role
by occurring regularly throughout narrative time. As Boyd [10] has shown, di昀昀erent linguistic
features exhibit meaningful changes over narrative time. In Figure 3, we plot the fraction of
structures and other artifacts over narrative time for our contemporary collection. As we can
see, we observe a preference for human-made things to appear towards the opening sections of
a narrative, suggesting that things function partially as “narrative establishments.” However,
in real terms the change is very slight, with a decline of roughly 15 total mentions of structures
between the 昀椀rst and 昀椀nal sections of an average narrative. In other words, evidence also
suggests that in addition to establishing narrative frames, structures and other artifacts also
play an infrastructural role in their continued presence over narrative time.




Figure 3: Frequency of structures and other artifacts over narrative time



3.3.4. Association
Finally, we explore collocate word types associated with structures to better understand how
they are semantically contextualized. As the theory of distributional semantics suggests, the
company that words keep has a strong in昀氀uence on their meaning [29]. We thus calculate the
likelihood of a word-type appearing in a sentence with a structure compared to sentences that
only contain other kinds of non-human-made entities (Table 6). Once again we use bookNLP’s
super-sense tags rather than condition on individual lexemes.
   As we can see, structures are most strongly associated with actions associated with contact
and motion and entities associated with substances and locations, while they are negatively cor-




                                                275
Table 6
Word types positively and negatively associated with structures across all genres in the contemporary
collection. G represents the likelihood ratio of each word type collocated with structure words.
                   Positive Association     G       Negative Association     G
                       verb.motion        313144   verb.communication      77159
                       verb.contact       200322   noun.communication      57418
                      noun.location        51015       noun.person         35933
                     noun.substance        39907      verb.cognition       35847
                     verb.perception      20811       noun.cognition       27290


related with actions of communication, cognition, and emotion. In other words, when readers
encounter structural things in 昀椀ction, they are considerably less likely to encounter moments
of a昀昀ect or cognitive re昀氀ection. Structural things are more likely to cause characters to move
and touch, not think and emote.


4. Discussion
Summarizing our 昀椀ndings to this point, we can say that according to our data the most common
kinds of things in 昀椀ction are structural in nature, i.e. human-made and supportive. These
may include rooms, houses, doors, windows, tables, roads, kitchens, walls, stairs, apartments,
among many other kinds of things. Such things are less likely to be modi昀椀ed and less likely
to be associated with a昀昀ective feelings. They are consistently deployed throughout narrative
time and they are more likely to facilitate corporeal rather than cognitive or communicative
behavior in characters.
   These 昀椀ndings raise challenges for some of the more prominent scholarly arguments that
have fallen under the heading of thing theory. Brown’s claim that 昀椀ctional things are important
because of their “labor of infusing manufactured objects with a metaphysical dimension” [11]
or Calvino’s claim that “in a narrative any object is always magic” (33) [13] do not 昀椀t well with
the semantic nature of the structural things that we have shown here. An individual door or
room may be magical or metaphysical (e.g. the door in Tieck’s Bluebeard’s Castle or Gregor’s
room in Ka昀欀a’s Metamorphosis), but broadly speaking such structural things are less likely
to be associated with ornamentation, a昀昀ect, or cognition. Their semantic inertia appears to
matter more to their identity rather than their individual a昀昀ective or descriptive depth.
   Similarly, Freedgood’s [17] assertion concerning the denotative value of things – the way
their value lies in their ability to point outwards to the world – also does not capture the broad
semantic behavior of 昀椀ctional things that we are seeing. While readers may connect these
objects to their historical life contexts, in terms of their narrative function within the texts
themselves it is far more likely that the rooms, houses, tables, and doors that predominate
serve as generic props rather than point deictically to rich historical or inner mental worlds.
The same holds for the longstanding critical interest in technological things [21, 27, 33]. While
the impulse to write about technologies like telephones, radios, and typewriters captures the
predominance of human-made objects within 昀椀ction since the nineteenth century, it fails to




                                                276
account for the most common kind of artifactuality within 昀椀ction, that of structural things.
   Barthes [6] has argued that such objects are in fact “narratively useless,” i.e. their function
is to resist interpretation and instead signify the idea of “referentiality” (143). They are there
merely to produce what he calls a “reality e昀昀ect.” Lamb [22] makes a similar point in arguing
that the value of 昀椀ctional things is their “irrelevance to any human system of value” (11). While
these theories address the semantic inertia of structural things (i.e. their supporting or back-
ground nature), they do not provide a framework for understanding why so many seemingly
useless things are so common in 昀椀ctional storytelling. Rather than see these highly frequent
objects as “useless” or “irrelevant” – akin perhaps to the idea of junk DNA – we would argue
that another theoretical framework outside of thing theory may provide a productive means
of understanding these objects’ narrative function.
   The framework we would suggest falls under the heading “embodied cognition,” an increas-
ingly studied (and still debated) framework within cognitive science [26] that has also found
increasing resonance in literary studies [2, 9, 14]. The key argument that embodied cognition
makes is that thinking is not localized in the brain but transpires through body-environment
interactions. Thought is distributed throughout one’s object world.
   One way to understand the predominance of structural things in 昀椀ction, then, would be as
a means of activating this idea of “embodied cognition” through 昀椀ctional narration. Structural
things shi昀琀 the focus, as Randall Beer, one of the early proponents of embodied cognition,
argued, “from accurately representing an environment to continuously engaging that environ-
ment with a body so as to stabilize appropriate co‐ordinated patterns of behavior” (97) [7]. The
strong corporeal and low decorative aspects of such objects may potentially produce, in Andy
Clark’s words, “a constantly available channel that productively couples agent and environ-
ment” (15) [15]. The persistent recurrence of such objects are thus neither narratively useless
nor to be understood principally as vehicles of introspection. Rather, they may be means of ac-
tivating an experience of “the extended mind,” enabling the experience of embodied cognition
in the minds of readers through these objects’ recurrent physical and semantically inert pres-
ence. Seen in this light, one of 昀椀ction’s modern social functions could be that it helps readers
activate the particular mode of thought known as embodied cognition.
   By empirically accounting for the types of things in 昀椀ction and their semantic identity across
large number of documents, our 昀椀ndings pose challenges to inherited critical theories about
the role of things in 昀椀ctional narratives. While those theories are undoubtedly valid for the
individual objects and works they address, they fail to account for the most predominant kinds
of 昀椀ctional things and their semantic behavior across large amounts of literature. Rather than
argue that such things are unimportant, we contend that it is highly important to account for
the most prevalent kinds of things in 昀椀ction if we are to understand the function of 昀椀ctional
things.
   While we suggest embodied cognition as one possible avenue for understanding the function
of such structural things, future work can test this theory further either through more text sam-
ples drawn from di昀昀erent cultural domains and languages or through empirical reader studies.
Work in embodied cognition has a long history of measuring human attention and problem
solving and many of these approaches could be productively applied towards understanding
reader behavior. The coupling of large-scale observational data with empirical reader studies
o昀昀ers an ideal synthesis to continue to better understand the social and psychological functions




                                              277
of 昀椀ctional things.


Acknowledgments
This research was generously supported by the Social Sciences and Humanities Research Coun-
cil of Canada (895-2013-1011).


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