=Paper=
{{Paper
|id=Vol-2607/paper4
|storemode=property
|title=Natural Language Processing for Literary Text Analysis: Word-Embeddings-Based Analysis of Zofka Kveder's Work
|pdfUrl=https://ceur-ws.org/Vol-2607/paper4.pdf
|volume=Vol-2607
|authors=Senja Pollak,Matej Martinc,Katja Mihurko Poniž
}}
==Natural Language Processing for Literary Text Analysis: Word-Embeddings-Based Analysis of Zofka Kveder's Work==
https://ceur-ws.org/Vol-2607/paper4.pdf
Natural Language Processing for Literary Text
Analysis: Word-Embeddings-Based Analysis of
Zofka Kveder’s Work
Senja Pollak1 , Matej Martinc1,3 , and Katja Mihurko Poniž2
1
Jožef Stefan Institute, Ljubljana, Slovenia
{senja.pollak, matej.martinc}@ijs.si
2
University of Nova Gorica, Nova Gorica Slovenia
katja.mihurko.poniz@ung.si
3
Jožef Stefan International Postgraduate School, Ljubljana, Slovenia
Abstract. In this paper we use word embeddings to analyse the corpus
of work of a Slovenian modernist writer Zofka Kveder. For a selection of
central concepts of her work, we compute the closest FastText embed-
dings. The interpretation shows that many of the word relations can be
interpreted in line with the findings in literary studies (e.g., woman is
discussed in relation to men and Catholicism), or open novel paths for
interpretation (e.g., woman in relation to European). On the other hand
we also point at some problems resulting from the lemmatization and
from using FastText embeddings.
Keywords: Digital literary studies · Word embeddings · Distant reading
· Gender · Zofka Kveder
1 Introduction
The computational methods have importantly enriched the studies of literary
history in the last two decades. However, it can also be stated that the digital
humanities depend in large part on literary studies [19]. Since 1980s, the femi-
nist theory and gender studies have played an important role in the analysis of
literary texts. Moreover, the feminist literary history has made visible a large
number of forgotten women authors through digitalization projects, such as The
Orlando Project (https://www.artsrn.ualberta.ca/orlando/), The Women
Writers Project (https://www.wwp.northeastern.edu/) and the Virtual Re-
search Enviroment NEWW Women Writers in History (http://resources.
huygens.knaw.nl/womenwriters/), which is focusing not only on collection of
Copyright c 2020 for this paper by its authors. Use permitted under Creative Com-
mons License Attribution 4.0 International (CC BY 4.0). DHandNLP, 2 March 2020,
Evora, Portugal.
women’s writings but especially on the collection of reception data. This illus-
trates the fruitful connection between feminist literary history and digital hu-
manities. Projects that connect computational methods and feminist approaches
with literary texts, enable better understanding of women’s roles, especially in
the literary life of earlier periods. Through the use of approaches such as distant
reading, developed by F. Moretti [15] in the Stanford Literary Lab, and by novel
data visualization and data analysis methods applied to large textual corpora,
new light can be shed on the work of forgotten or neglected women writers.
The writings of women have always been an integral part of the literary field
although they encountered many obstacles caused by the male dominance [2].
Feminist digital literary studies have impacted the field of digital humanities, but
regrettably also here, their contributions have not always been recognised and
acknowledged [20]. Recent studies [17,4] prove how feminist approaches within
digital humanities enable new findings and more complex understanding of the
literary history. Also in our work, we investigate a female author, and position
our work in the field of digital humanities in combination with with the femi-
nist literary history and gender studies. We focus on the work of Zofka Kveder
who was one of the most important female writers in the multicultural space
of Habsburg Empire. Zofka Kveder’s work has been previously transformed to
digitalized form and identified as a good source for digital humanities investiga-
tions [12], but the presented work is the first actual study analysing the work
with digital humanities and natural language processing methods.
In this paper, we test how natural language processing methods can facilitate
the investigation of a literary text, in particular how using word embeddings can
reveal interesting relations between concepts in the work of Zofka Kveder. Word
embeddings are vector representations of words, where each word is assigned a
real-valued vector in a vector space. Due to the distributional hypothesis (see
Zellig Harris [7]), which states that words used in similar context will have similar
meanings, embeddings can capture a certain degree of semantics by translating
semantic relations in text into vector space relations. Word embeddings have
been previously applied to literary text corpora. For example, Grayson et al. [6]
use them to compare the characters in 19th-century fiction by the authors Jane
Austen, Charles Dickens, and Arthur Conan Doyle, while Wohlgenannt et al. [21]
test several word embeddings methods on the task of extracting a social network
for literary texts, specifically on the series of fantasy novels. In our experiments,
we train FastText embeddings [1] on the corpus of works of Zofka Kveder and for
selected concepts identify twenty nearest semantic neighbours according to the
cosine similarity between the embedding vectors. These are then interpreted from
a literary perspective, showing the potential of simple computational approaches
to literary investigation, as well as some deficiencies of automated methods.
2 Corpus of Zofka Kveder
Zofka Kveder (1878-1926) was a multilingual and multicultural author who lived
in three Central European capitals: Ljubljana, Prague and Zagreb and wrote in
three languages: Slovenian, Croatian and German. Many of her works were pub-
lished in newspapers and literary magazines in the Central and South-Eastern
Europe in Czech, Slovak, Bulgarian, Serbian, Polish and Serbian language. She
was also a cultural mediator and an ardent feminist. In most of her stories,
a female character in various roles is in the foreground. She also touched on
the concept of free love, which was an important issue at the time, and acknowl-
edged the problems of forced marriages, women’s urges, illegitimate motherhood,
abortion, suicide, prostitution, early death at childbirth and many other themes
from the lives of women. As many authors from the late 19th and early 20th
century, Zofka Kveder depicted the incompatibility of women’s emancipation
with marriage and motherhood, and criticized the double moral of the middle-
class society, which could not accept an unmarried woman to enjoy sex without
feelings of guilt [14].
She also looked for concrete possibilities that would allow women to overcome
their position as the Other, to change their relationship with their own bodies
and to overcome feelings of guilt and uselessness, which, as she demonstrated,
could lead to the disintegration of identity or even death. Having opted for
stylistic pluralism, Kveder shaped her narrative using naturalist-realistic stylis-
tic devices, while also feeling an affinity for stylistic procedures typical of New
Romanticism. Her works have been translated to many European languages,
including Bulgarian, English, German, Polish, Czech.
The corpus in our study contains all Kveder’s Slovenian writings: two novels,
two plays, two one-act plays, some dramatic scenes, a large number of short
stories and tales and articles (literary reviews, feminist writings, etc.). The corpus
was published in five volumes of the Collected works of Zofka Kveder - as printed
and electronic books edited by K. Mihurko Poniž [10,9]. In total, the corpus
contains 1,217,517 tokens.
3 Selected concepts
For our analysis, we have selected 12 concepts (words): ženska [woman], žena
[wife/woman], moški [man], mož [husband/man], moderen [modern], duša [soul],
pijanec [drunkard], ljubezen [love], otrok [child], emancipiran [emancipated], po-
tovati [to travel], mati [mother].
The concepts have been selected according to the prevailing topics in Kveder’s
works. The selection criterion was also Kveder’s relationship to the concepts of
the so-called Wiener Moderne (Viennese modern age). In the last decade of the
19th century and in the first decade of the 20th century in the majority of the
European literatures different stylistic formations had been developed that are
associated under the umbrella-term of the literary modernity (cf. Le Rider [11]).
We wanted to find out how Kveder positioned herself and her literary figures
towards the concept of “modern”. The authors of the Viennese modern age re-
visioned the concepts of gender roles, therefore the concepts of woman, man and
love were chosen. The femaleness was in the majority of writings of the mod-
ern age still connected with the motherhood, therefore we were interested how
Kveder connected different topics around this thematic field and consequently
if we can conclude that she represented the conservative or progressive views on
this problem (concepts of mother and child). The writers who belonged to the
literary modernism (especially to the literary currents of symbolism and new ro-
manticism) developed new views on the relationship between body and internal
world - in Slovenian language the word soul was used at that time for the indi-
vidual’s psyche. In the feminist but also in the literary writings Kveder reflected
upon women’s emancipation (therefore we selected the concept of emancipa-
tion), which was also one of the central topics of the modern age. Since in the
late 19th and early 20th century women traveled and explored new worlds more
often than ever before, we were also interested, how the concepts of travel and
migrations were coded in Kveder’s texts (concept of travel). The concept of the
drunkard was chosen because of Kveder’s strong (autobiographical) interest in
the topic of alcoholism.
4 Method
Even if usually word embeddings are trained on very large corpora, there are sev-
eral studies that show that embeddings can also lead to useful results on smaller
text collections. For example, a recent study by Diaz et al. [5] suggests that
leveraging embeddings trained on a large general corpus for modelling semantic
relations on a specialized corpus is problematic due to strong language use vari-
ation. The study shows that embeddings trained only on a small topic specific
corpus outperform non-topic specific general embeddings trained on very large
general corpora for a somewhat specific task of query expansion in specialized
text. Similar, FastText embeddings trained on small domain corpora were used
in Pollak et al. [18]. Since we are also dealing with a specialized historical text
written by a single author known for its distinct writing style, we follow this line
of research and train embeddings only on the author’s text.
To counteract the negative affects of a small training corpus, we use Fast-
Text embeddings [1] as they are capable of capturing subword information and
modeling of affixes and suffixes by representing a word as an average of its char-
acter n-grams of specific length. This allows the model to compensate for the
lack of available semantic information due to small corpus size by leveraging also
morphological similarity, which in many cases translates to semantic relatedness.
Also, since Slovenian is a morphologically rich language, FastText embeddings
are trained on a lemmatized corpus of Zofka Kveder’s texts. Lemmatization was
employed in order to prevent the scenario in which the majority of nearest seman-
tic neighbours we want to obtain for each seed concept would be different forms
of the input concept. Text was lemmatized using Lemmagen lemmatizer (Juršič
et al., 2010). After that, for each of the chosen concepts we obtain 20 nearest
semantic neighbours according to the cosine similarity between the embedding
vectors. The selected sets are then used for literary investigation, presented in
next section.
Table 1. 20 closest word embeddings for 12 seed concepts in Slovenian (asterisk *
denotes words which were incorrectly lemmatized; in some cases the correct lemma is
given in square brackets).
Seed word 20 closest semantic neighbours (Slovenian)
ženeva, evropejec, moški, mošnja, mera,
žena, moštvo, moš*, farizej, razmera,
ženska
konkurent, klerikalec, klerikalizem, konkurenca, modistinja,
konkurenčen, ovsenjak, bošnjak, filolog, možitev
mož, ženin, ženitev, možen, sina,
zmožen, uboštvo, možitev, rodbina, ženska,
žena
neomožen, možev, ženeva, moštvo, omož* [omožen],
družina, milodar, evropejec, naključje, vdova
joški, refoški, ženski, filološki, kmetiški,
ženska, loški, spol, miški, bloški,
moški
psihološki, kakršen, fanuški*, ženstvo, emancipiran,
šiški [Šiška], evropejec, neženski, privilegiran, moštvo
defravdant, vdova, žena, ženin, vnuk,
sina, tesin*, nadlega, vnukinja, vdov,
mož
zbera, vnovič, ženitev, oče, sin,
sorodništvo, služinčad, guvernant, rojak, starš
monumentalen, operen, uporen, efekten, tipičen,
uvoden, orientalen, obnošen, vzhoden, mody*,
moderen
originalen, buben, ošpičen, patetičen, okusen,
koncerten, teren, impozanten, asketičen, frapanten
hrepenenje, dušeč, srce, hrepeneč, verujoč,
čuteč, vesoljstvo, grenkoba, atom, slepota,
duša
toplina, suša, tesnoba, mrzlota, napetost,
hrepeneti, omamljenost, gorkota, pesimizem, sočutje
jeruža, žganec* [žganje], dedec, indijanec, galicijanec,
žganjar, sodovka, pivec, umazanec, košir,
pijanec
kregar, debevčev, grunt, podgradar, hribovka,
oštir, mešičkovka, pokora, matijec*, kristjan
zvestoba, vkljub, neljub, vdan, samoljuben,
ljuta, samoljubje, preljubezniv, preljub, zaljubljenost,
ljubezen
zvest, verujoč, sočutje, tesnosrčen, dobrota,
lažniv, objetje, milina, poljuben, ponižujoč
sirotica, vnuk, vnukinja, angel, njivica,
odrasel, šib, lenoba, črviček, ubožica,
otrok
angela, dekletec, mezinec, snah, sinček,
terezinka, rajnki, deca, sinka, sinek
talentiran, improviziran, absolviran, izoliran, privilegiran,
karakterizirati, cimperman, kompliciran, civiliziran, filolog,
emancipiran
tradicionalen, respekt, naturalizem, rezerviran, konvencionalen,
tiranizirati, individualiteta, individualen, afektiran, manir
pestovati, službovati, izposlovati, posvetovati, odsvetovati,
prorokovati, zborovati, posredovati, gostovati, poizvedovati,
potovati
nazadovati, vasovati, učinkovati, obrekovati, obiskovati,
obedovati, nadzorovati, napredovati, vojskovati, tekmovati
obubožati, hči, obdržati, omehčati, poizkušati,
svarilo, obljubovati, hčerin, dedov, starati,
mati
očenati* [očenaš], pokopavati, hčerkin, prikrajšati, vnuk,
objokovati, odklepati, zbližati, sinek, obupati
Table 2. 20 closest word embeddings for 12 seed concepts in English translation (as-
terisk * denotes words which were incorrectly lemmatized in Slovene).
Seed word 20 closest semantic neighbours (English translation)
geneva, european, man, pouch, measure,
woman/wife, manhood/team, husband*, pharisee, situation,
woman
competitor, cleric, clericalism, competition, milliner,
competitive, oatcake, bosniak, philologist, wedlock
husband, groom, marriage, possible, son,
capable, poorness, wedding, relatives, woman,
wife/woman
unmarried, husband’s, geneva, maleness, marry*,
family, charity, european, coincidence, widow
boobs, refošk, female, philological, peasant,
woman, loški, gender, mice, bloški,
man
psychological, kind, fanuški, womanhood, emancipated,
šiška, european, unmarried, privileged, maleness
defalcator, widow, wife, groom, grandson,
son, tesin*, problem, granddaughter, widow,
husband/man
gather, again, marry, father, son,
kinship, domestics, governess, compatriot, parent
monumental, opera, rebellious, showy, typical,
introductory, oriental, worn-out eastern, mody*,
modern
original, bubna, naughty, pathetic, tasty,
concert, terrain, imposing, ascetic, fascinating
longing, suffocating, heart, yearning, believing,
feeling, universe, bitterness, atom, blindness,
soul
warmth, drought, anxiety, coldness, tension,
longing, stoned, bitterness, pessimism, compassion
spirit, alcohol, buster, indian, galician,
distiller, soda, drinker, dirty, košir,
drunkard
kregar, debevec’s, estate, podgradar, highlander,
innkeeper, mešičkovka, penance, matijec*, christian
fidelity, despite, undesirable, devoted, self-impetuous,
angry, self-centeredness, kindest, dearest, infatuation,
love
faithful, believing, compassion, coldhearted, kindness,
lying, embracement, grace, arbitrary, humiliating
orphan, grandson, granddaughter, angel, field,
adult, rod, laziness, worm, pauper,
child
angel, girl, little finger, daughter-in-law, little son,
terezinka, deceased, children, little son, little son
talented, improvised, absorbed, isolated, privileged,
characterized, cimperman, complicated, civilized, philologist,
emancipated
traditional, respect, naturalism, reserved, conventional,
tyrannize, individuality, individual, affected, manner
hold in arms, serve, arrange, consult, advise against,
prophesy, convene, mediate, host, inquire,
to travel
regress, feast, effect, slander, visit,
dine, control, progress, wage war, compete
loose all possessions, daughter, retain, soften, try,
warn, promise, daughter’s, grandfathers, grow old,
mother
Lord’s prayer, bury, daughter’s, deprive, grandson,
grieve, unlock, bring together, little son, despair
5 Analysis and discussion
In Table 1 we present the results of experiments and in Table 2 the English
translations. In this section, we interpret selected concepts and relations from
the perspective of literary studies, and reveal some limitations of the method.
The concept woman (see table rows 1 and 2) is placed in a relationship with
man (man, husband, groom) and with Catholicism: Pharisee, cleric, clericalism.
Words related to writer’s family situation (family, widow, son) also appear.
In connection with the concept woman, there is also the word milliner, which
indicates a common women’s profession in the modern age. The connection with
the word European is also interesting because literary studies have not discussed
it yet.
In the concept of emancipated, no word appears in direct connection with a
woman. The concept of mother appears in connection with daughter, which is ex-
pected, given the frequent topic of the mother-daughter relationship in Kveder’s
writings. The concept mother connects with words that express emotions asso-
ciated with suffering: to bury, to grieve, to despair. The literary studies on the
topic of motherhood in Kveder’s work connected Kveder’s work with negative
representations of motherhood [13].
A man is positioned in the relationship to a woman (wife, marriage) and
in his family role (son, grandson, father, parent, kinship). Interesting is the
connection with the word gender, which does not occur in resulting words for
the the seed concept woman. The concept love is associated with fidelity/loyalty
and emotions. Surprisingly, it does not connect with the body, although this
was discussed as a frequent topic in Kveder’s oeuvre in the field of literary and
gender studies [8].
The concept of modern is associated with words such as rebellious, effec-
tive, original but also pathetic, imposing, ascetic and fascinating, which are the
expected connections according to previous research of Kveder’s writings. The
connection with the Oriental is interesting and calls for further research. The re-
lation with the concept soul (longing, heart, compassion) are unsurprising since
this concept was often discussed in the modern age. However, the connection
with the word atom is interesting and unexpected.
Subword information, which influences the similarity in FastText embed-
dings, generally improves the semantic modelling in morphologically rich lan-
guages and small corpora, as it helps with finding semantically similar con-
cepts with similar morphological structure. For example, similar lexemes in žena
[wife], ženin [groom], ženitev [marriage] are reflecting also semantic similarity of
words. On the other hand, the results indicate that this feature can also lead to
strong correlations between semantically (mainly) unrelated words containing
many common characters (e.g., strong correlation between ženska (woman in
Slovenian) and Ženeva (Slovenian name for the city in Switzerland)). An inter-
esting example is also ljubezen [love], where we can find many etymologically
related words with common lexemes, which can be easily interpreted as seman-
tically related, such as samoljuben [self-centred], samoljubje [self-centeredness],
preljubezniv [kindest], but on the other hand we have words with similar subword
information that are not closely semantically related (e.g. poljuben [arbitrary]).
Another aspect related to string similarity is related to word types. We can
notice that the part-of-speech (POS) of seed words and returned words is to a
large extent preserved. In our case the majority of seed words are nouns, and
corresponding returned embeddings return nearly only nouns, while when adjec-
tives or verbs were selected as seeds, the related words also belong mainly to the
respective POS categories. This is due to stronger association between words
with the same characteristic word type affixes. For example, the seed adjec-
tive emancipiran has returned the set of semantically closest words talentiran,
improviziran, absolviran, . . . , while the verb potovati is associated to verbs pesto-
vati, službovati, etc. However, when a noun has a typical verb ending (e.g. mati ),
there are many verbs in the returned list. Even if in general grouping of words in
relation to their POS can be interpreted as a feature, we found that in our study
(on a small corpus) this could be a source of confusion and that nouns provided
more interesting and reliable results than verbs and adjectives. Nouns would also
be our first choice for selection of seed words for future analysis of literary works
in Slovenian language with FastText embeddings. Another thing that made the
interpretation of results harder are mistakes in the lemmatization. For example,
first name Joško was lemmatized into joške (Slovenian for boobs), showing that
named entities should be marked or better handled in lemmatization.
6 Conclusion and future work
In this paper, we investigate how natural language processing methods can fa-
cilitate the investigation of literary work. We have trained FastText embeddings
on the corpus of the text of Zofka Kveder who was a principal Slovenian mod-
ernist, multilingual and multicultural author and a feminist. We have selected
twelve concepts (words), according to the prevailing topics in Kveder’s works
and in relationship to the concepts of the so-called Wiener Moderne (Viennese
modern age). For these words, we have computed twenty nearest semantic neigh-
bours according to the cosine similarity between the embedding vectors. These
were then interpreted from a literary perspective, showing the potential of sim-
ple computational approaches to literary investigation. From the point of view
of the research of Zofka Kveder’s work, the results of our research confirm the
findings of literary history studies, and also open new research directions (e.g.
the relation between woman and European, and modern and Oriental), which
means that computer analysis provides interesting results that can be a useful
approach in literary studies. In future work, we plan to enlarge the set of con-
cepts, investigate how to remove noise by using improved lemmatization, testing
the results without lemmatization and recognizing named entities. In addition to
observing similarities between concepts, word embeddings allow for investigating
analogies, which could be very interesting when applied to literary texts. Fur-
ther, we plan to use the methods on larger literary corpora, which would allow
for embeddings-based analysis of differences between authors, authors’ gender
(e.g. male vs. female authors in the same period) and diachronic based studies,
which would allow to analyse how certain concepts evolved during time. Last but
not least, we will analyse different word embeddings methods (w2v, GloVe,...) to
analyse strengths and weaknesses of different methods, and compare the results
to statistical word association measures, such as PMI [3] and PPMI [16].
Acknowledgements
The work presented in this paper has been supported by European Unions
Horizon 2020 research and innovation programme under grant agreement No.
825153, project EMBEDDIA (Cross-Lingual Embeddings for Less-Represented
Languages in European News Media). The authors acknowledge also the financial
support from the Slovenian Research Agency core research programme Knowl-
edge Technologies (P2-0103) and the research programme Historical Interpreta-
tions of the 20th century (P6-0347). The authors also acknowledge the COST
Action Distant Reading (Grant No. CA 16204).
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