=Paper=
{{Paper
|id=Vol-2604/paper9
|storemode=property
|title=Associative Verbal Network of the Conceptual Domain БІДА (MISERY) in Ukrainian
|pdfUrl=https://ceur-ws.org/Vol-2604/paper9.pdf
|volume=Vol-2604
|authors=Olena Levchenko,Oleh Tyshchenko,Marianna Dilai
|dblpUrl=https://dblp.org/rec/conf/colins/LevchenkoTD20
}}
==Associative Verbal Network of the Conceptual Domain БІДА (MISERY) in Ukrainian==
https://ceur-ws.org/Vol-2604/paper9.pdf
Associative Verbal Network of the Conceptual Domain
БІДА (MISERY) in Ukrainian
Olena Levchenko1[0000-0002-7395-3772], Oleh Tyshchenko2[0000–0001–7255–2742] and Marianna
Dilai3[0000-0001-5182-9220]
1,3Lviv Polytechnic National University, Lviv, Ukraine
2University of Ss. Cyril and Methodius in Trnava, Trnava, Slovak Republic
1levchenko.olena@gmail.com, 2olkotiszczenko@gmail.com, 3marian-
nadilai@gmail.com
Abstract. This paper presents a comprehensive study of the associative verbal
network of the conceptual domain БІДА (MISERY) in the Ukrainian language.
The associative test is carried out in order to obtain statistical and quantitative
data necessary for modeling the conceptual domain БІДА (MISERY) and estab-
lishing the areas of its intersection with the related concepts of ENVY and
GREED. Determining the ‘associative’ distance between the concepts (the index
of mutual associative relation) and visualizing the test results we identify typo-
logically common and distinct plots within the associative verbal network. The
analysis of collocations in the GRAC corpus allowed us to identify associative
statistical patterns of their modeling using the latest quantitative, cognitive and
ethnosemiotic methods, and describe the taxonomy of the frames. Furthermore,
applying Mutual Information score we revealed the ranges of intersection, gra-
dation, opposition, areas of relative and absolute frequency, typicality, unique-
ness, gender markedness, etc., of the responses to the stimulus БІДА (MISERY).
Keywords: associative verbal network, associative test, conceptual domain mod-
eling, text corpus, associative distance between concepts, Ukrainian.
1 Introduction
Researchers claim that the associative test "allows a researcher to confirm the psycho-
logical relevance of theoretical assumptions, that is, to represent the associative net-
work of senses ... as a reflection of hierarchical conceptual structures in speaker’s mind"
[1], and reactions to a particular stimulus can be viewed as the reflection of correspond-
ing conceptual structures that are to a certain extent accompanied by emotions and eval-
uations in accordance with the speaker’s individual conceptual worldview. In addition,
the associative test is one of the effective ways of exploring linguistic consciousness
and its national and cultural specificity, since it explicates the lexical semantic relations
and linguistic stereotypes which are objectively given in the speaker’s mind [2]. Ac-
cording to the authors of Polski slownik asocjacyjny, it is aimed at analyzing the ways
of describing, interpreting and perceiving the world, its evaluative categorization by the
native speakers, to reproduce the “kulturowo utrwalony system znaczeń” reflecting the
mental structures that function in the linguistic consciousness [3].
There are a number of associative dictionaries and associative tests in Ukrainian
psycholinguistics, including The Dictionary of Associative Norms of the Ukrainian
Copyright © 2020 for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Language by N. Butenko [4]. N. Butenko conducted an experiment in 1974-1975 with
the students of Lviv higher educational institutions aged from 18 to 30 years, whose
mother tongue was Ukrainian, believing that students were “a mature and at the same
time appropriate group of the population for a mass test” [4]. N. Butenko argued that
occupation and gender had little impact on respondents' answers [4]. The questionnaire
contained 133 stimulus words, based on Kent-Rozanov's list and supplemented with
variant equivalents of words on that list [4]. Unfortunately, the reactions are not dis-
tributed by gender and professional field in that dictionary. The author of the dictionary
also made an interesting note that the weather data had been recorded, however, that
information was not interpreted in any way.
In 1989 N. Butenko's Dictionary of associative attributes of nouns in Ukrainian was
published [5], combining the idea of associative and attributive dictionaries. This dic-
tionary is based on the results of AT (hereinafter referred to as the associative test) with
200 respondents receiving a list of 35-40 nouns, to each of which five to seven attributes
were to be provided (except pronouns and ordinal numbers) [6]. The preface states that
the stimuli were the most commonly used nouns of the Ukrainian language [6], how-
ever, it should be noted that this statement is rather doubtful. The stimulus words in-
cluded 816 nouns [5], such as абажур, абрикос, аварія, автобус, автомат,
автомобіль, автор, агітатор, агроном, адвокат, адреса, айстра, академік
(lampshade, apricot, accident, bus, vending machine, car, author, agitator, agrono-
mist, lawyer, address, aster, academician), etc. It is obvious that the stimulus words do
not belong to “the most common nouns”.
The Ukrainian-language material is also presented in the Slavic Association Dic-
tion-ary: Russian, Belarussian, Bulgarian, Ukrainian [7]. In 2007, S. Martinek pub-
lished the Ukrainian Associative Dictionary [8]. The author used the list of 841 stimuli,
“where words of different parts of speech are extensively represented: nouns, adjec-
tives, verbs, adverbs, etc. This list includes words from the previous Ukrainian associ-
ative dictionaries [8]. This dictionary contains such stimuli as бідний, бідність,
бідніти, бідно (the poor, poverty, to become poor, poorly), which makes it impossible
to trace the stability / variability of associative reactions. In addition, there are a number
of ‘specialized’ associative dictionaries [9].
The approach proposed in this study makes it possible to find out the specificity of
the associative verbal network (hereinafter referred to as AVN), in view of the statistics
and taxonomy of the frame structures and inter-conceptual associative relations.
I. Sternin and Z. Popova claim that “the cognitive interpretation of the results of asso-
ciative tests can be carried out by describing psycholinguistic significance, but it can
also be carried out directly by the direct cognitive interpretation of associations" [10].
In general, our approach is theoretically and methodologically grounded in the experi-
mental psycholinguistic research [11; 12; 13; 14; 15], cognitive science findings sug-
gesting representation of concepts as frames [16] and exploitation of such findings in
NLP, in particular, creating a network (or a graph) of concepts, and automatically learn-
ing the different patterns of association between concepts [17].
The results of the associative test conducted in 2019 are the material of this study.
The characteristic feature of this AT is the fact that it was carried out ‘without coercion’,
in other words, the test was mostly done by the Internet users of their own free will:
194 respondents, including 99 women and 95 men of the following age groups: 14-18
– 9.79%, 19-24 - 50%; 25-34 - 14.43%; 35-43 - 12.89%; 44-59 - 11.86%; 60-74 -
1.03%. A few more people out of those who have completed the test specialize in hu-
manities. The respondents were given 67 stimuli, including біда, бідувати; бідна як;
бідний як (misery, to be miserable; miserable as (f); miserable as (m)).
2 The Associative Test Methodology
Describing the methodology for conducting the AT, the Russian researcher A. Baranov
emphasizes that respondents should give responses on the spot. In our opinion, N. Bu-
tenko's instruction is indicative in this sense: “<…> After every stimulus word is given
to you, write down the first word that comes to your mind in connection with the stim-
ulus. Then move on to the next word. Always answer in one word; do not omit the
words <...>. Do not look away, do not look in the neighbor's questionnaire, do not ask
him/her. It is important that your answer is individual. Work quickly until you complete
the entire questionnaire” [4]. Presenting the methodology for conducting AT, O. Ula-
novich emphasizes that respondents are to answer within a limited period of time, but
the author does not indicate the exact time [18]. S. Martinek states that the respondent
spent 5-7 seconds on each response during her experiment [8]. The remarks about ‘not
thinking’ and omitting words are symptomatic in this context. Unfortunately, an exper-
imenter cannot claim that a respondent gave the response ‘without thinking’ that it was
the first word that came to mind. In our opinion, indicating non-omission puts a certain
pressure on a respondent. The outcomes of our testing show that the respondents pro-
vided responses without omitting stimuli, mostly until the middle of the given list, by
the end of the list the number of responses decreased. Even at the beginning of the list,
some respondents put ‘no association’ or a dash mark indicating no response. Thus, 194
people took part in our experiment, however, for example, the stimulus біда (misery)
received 171 responses.
Another problem is the ‘regularity’ or even ‘normativity’ of responses. A. Goroshko
states that association is “a relation formed under certain conditions between two or
more mental entities (feelings, acts, perceptions, ideas, etc.); the effect of this relation
– the actualization of association – is that the emergence of one member of association
regularly triggers the emergence of the other one (others)” [19]. The statement concern-
ing the regularity of reactions raises some doubts, in particular about the ‘degree’ of
regularity. In this regard, it is important, according to Yu. Ulyanov; “... the perceived
word (stimulus) generates in our mind a boundless system of relations and relationships
that reflect the images of objects, phenomena, concepts, actions and words, our emo-
tional state at that moment, as well as the life experience of the individual” [20]. In
other words, the regularity of emergence of certain associations may be peculiar to a
particular period of a linguistic community existence due to the shared experience of
the speakers. To a certain extent, this is proved by comparing the results of associative
tests with native speakers, but in different periods of time. The dynamics of responses,
in particular, may be driven by the dynamics of the semiotic system. In addition, we
can speak about the typical appearance of certain words in response to certain stimuli,
since they belong to the relevant frames.
3 Results and Discussion
The specificity of the proposed method is to determine the associative distance between
concepts by analyzing data on their mutual associations (the index of mutual associative
relation) and visualize the results of the associative test, which makes it possible to
identify such common plots. Figure 1. presents the AVN plot studied based on the
weight of each of the vertices.
Fig. 1. Associative verbal network (AVN) of the conceptual domain БІДА (MISERY)
Thus, the stimulus біда (misery) received a total of 171 responses of the Ukrainian
respondents, including 84 unique ones. In this AT, in general, the diversity index of
female and male responses to the stimulus біда (misery) is approximately the same (f
0.53 / m 0.6). It has been revealed that male and female responses often are the same
(see Fig. 2).
Figure 3. presents the most frequent responses to the stimulus біда (misery) (dis-
tribu-tion by gender). The most frequent response to the stimulus біда (misery) given
both by women and men is the synonymous response горе (grief) (f 18.56%, m
10.81%), which belongs to the descriptive frame and makes up 15.20% of the total
number of responses. The following reactions are also synonymous: лихо (disaster) (f
2.06, m 6.76, total 4.09), нещастя (unhappiness) (f 2.06, m 4.05, total 2.92), лишенько
(dis-aster) (f 1.03, m 0.00, total 0.58). Antonymic reactions are also given: щастя
(hap-piness) (f 1.03, m 0.00, total 0.58), радість (joy) (f 1.03, m 0.00, total 0.58), не
біда (no trouble) (f 1.03, m 0.00, total 0.58). Interestingly, only women responded anto-
nymically.
The respondents also responded using чорна (black) (f 13.40, m 5.41, total 9.94).
The attribute чорна (black), which belongs to the descriptive axiological frame, can be
considered a set one, as evidenced by the GRAC corpus data: чорна біда (black misery)
– 0.03 per million, біда чорна (misery black) – 0.03 per million [21].
Fig. 2. Male and female responses to the stimulus біда (misery)
On the list of responses, we can find evaluative attribute страшна (terrible) (f 3.09, m
0.00, total 1.75). In the GRAC corpus, the frequency of the phrase страшна біда (ter-
rible misery) is 0.16 per million and, as for біда страшна (misery terrible), it is 0.02
per million. In the analyzed associative test on the stimulus біда (misery) the following
responses were given just once: незвідана (unknown) (f 1.03, m 0.00, total 0.58), доб-
ра (good) (f 1.03, m 0.00, total 0.58); велика (large) (f 0.00, m 1.35, total 0.58); погана
(bad) (f 0.00, m 1.35, total 0.58); ой (oh) (f 1.03, m 0.00, total 0.58), etc.
Fig. 3. Most frequent responses to the stimulus біда (misery) (Gender Distribution)
It should be noted that the corpus data are compared (see Table 1), although the fre-
quency of occurrence, or rather the occurrence order, of the corresponding word com-
binations is different from those in the associative test. Table 1. shows collocations with
a component біда (misery). The analysis of the corpus data shows that the collocation
велика біда (great misery) is of the highest absolute frequency collocation model AD-
JECTIVE + NOUN. However, according to the results of the associative test, the most
frequent responses are чорна (black), страшна (terrible). The methods currently avail-
able to determine ‘candidates’ for collocations do not allow us to obtain the desired
result in terms of determining metaphorical expressions. Today, different methods are
used to identify collocations. V.P. Zakharov and M.V. Khokhlova state that most often
such methods as MI-score, t-score and log-likelihood are used to detect collocations
[22]. The researchers claim that the simplest way to detect a collocation pair is based
on the relative frequency, which gives the most common collocation associations, how-
ever, this method has a number of drawbacks. Considering this, it is obvious that one
of the options could be Mutual Information score (MI) [23]. E. Yagunova and L.
Pivovarova concluded that the lists of collocations obtained using MI and t-score differ
fundamentally: MI is the best one for distinguishing object names, terms, complex nom-
inations; t-score, on the contrary, works better when distinguishing between ‘lexical
bundles’ (derivative functional words, discourse markers) and ‘set expressions’ [24]. A
word combination is considered to be statistically significant if the MI score is greater
than 1, but the COCA corpus states that the semantic relations between words can only
occur if the MI score between them is at least 3. Thus, for example, O. Shyshygina
accepts a low MI score range of 1.0–2.9, an average one of 3.0–5.0 and a high one of
5.1 and above [25]. The analysis of the data obtained from the GRAC corpus (see Table
1) shows that it is impossible to detect metaphorical expressions by the abovementioned
methods without ‘manual intervention’.
Table 1. . Candidates for collocations (the GRAC corpus).
The num- The T-score MI MI3 log min. log- MI.log_f
ber of num like- sensi- Dice
combina- ber li- tivity
tions of hood
can-
di-
date
s
великий 550 405305 22.436 4.5292 22.735 2412.5 0.0013 5.3859 28.587
42 3 81 4605 6 3 32
тяжкий 120 22828 10.831 6.4829 20.296 842.32 0.0046 6.3402 31.090
98 7 75 581 7 7 95
новий 116 241141 9.4545 3.0330 16.749 284.53 0.0004 3.8323 14.443
4 6 02 659 8 4 94
страшний 111 35500 10.337 5.7334 19.322 665.22 0.0031 5.8931 27.053
63 8 31 927 3 0 41
найбіль- 83 43587 8.8292 5.0180 17.768 416.90 0.0019 5.2946 22.233
ший 7 2 10 955 0 8 94
людський 82 93804 8.4466 3.8947 16.609 290.05 0.0008 4.4908 17.210
1 8 89 971 7 2 43
невеликий 74 37600 8.3454 5.0656 17.484 376.41 0.0019 5.2594 21.870
5 0 51 601 7 7 67
справжній 72 86237 7.8880 3.8285 16.168 248.49 0.0008 4.3975 16.426
1 0 35 723 3 6 02
головний 54 106388 6.4976 3.1105 14.620 137.46 0.0005 3.7437 12.464
4 0 28 685 1 1 83
гірка 34 4919 5.7813 6.8779 17.052 257.03 0.0013 5.1851 24.453
|гіркий 7 1 83 729 2 8 35
гірший 33 10752 5.6345 5.7066 15.795 196.46 0.0012 4.8905 20.123
7 7 46 919 8 7 78
чорний 20 114615 2.9659 1.5700 10.213 17.011 0.0001 2.2235 4.7801
7 9 94 93 7 9 6
In addition, the results of the AT reveal reactions related to the descriptive possessive
frame: чия (whose) (f 1.03, m 0.00, total 0.58), своя (own) (f 1.03, m 0.00, total 0.58),
моя (mine) ( f 1.03, m 0.00, total 0.58), мене (me) (f 1.03, m 0.00, total 0.58), його
(his) (f 0.00, m 1.35, total 0.58).
The responses given below are of high frequency: смерть (death) (f 5.15, m 8.11,
total 6.43), смерть, втрата (death, loss) (f 1.03, m 0.00, total 0.58), смерть, важка
хвороба (death, serious illness) (f 1.03, m 0.00, total 0.58), незворотна втрата здо-
ров’я (irreversible health loss) (f 1.03, m 0.00, total 0.58). They are referred to the
definitive type (it can be considered that the respondents have responded using the con-
cepts that for them are examples of біда (misery), such as “біда – це …”(misery is…)).
The definitive reactions also include: хвороба (illness) (f 4.12, m 6.76, total 5.26),
тяжка хвороба (severe disease) (f 1.03, m 0.00, total 0.58), проблема (problem) (f
1.03, m 2,70, total 1,75), проблеми (problems) (f 0.00, m 2.70, total 1.17), життєва
проблема (life problems) (f 1.03, m 0.00, total 0.58); війна (war) (f 1.03, m 1.35, total
1.17), становище (situation) (f 0.00, m 1.35, total 0.58); сесія (session) (f 0.00, m
1.35, total 0.58); провалля (failure) (f 1.03, m 0.00, total 0.58); пожежа (fire) (f 0.00,
m 1.35, total 0.58); наряд (duty) (f 0.00, m 1.35, total 0.58); корупція (corruption) (f
1.03, m 0.00, total 0.58); загроза (threat) (f 0.00, m 1.35, total 0.58); забагато вдало
розташованих дебілів (too many well-placed jerks) (f 0.00, m 1.35, total 0.58);
життя (life) (f 0.00, m 1.35, total 0.58); гроза (thunderstorm) (f 1.03, m 0.00, total
0.58); голод (hunger) (f 0.00, m 1.35, total 0.58); аварія (accident) (f 0.00, m 1.35,
total 0.58), etc.
A number of responses to the stimulus біда (misery) belong to the scenario frame
(they are also sometimes referred to as syntagmatic type reactions), such reactions are
the activation of corresponding phraseological units in respondents’ memory: не
приходить одна (does not come alone) (f 2.06, m 6.76, total 4.09); не ходить одна
(does not walk alone) (f 3.09, m 0.00, total 1.75); сама не ходить (does not walk alone)
(f 1.03, m 0.00, total 0.58); приходить не одна (does not come alone) (f 0.00, m 1.35,
total 0.58); прийшла (came) (f 1.03, m 0.00, total 0.58); прийде (will come) (f 1.03, m
0.00, total 0.58); не приходить сама (does not come alone) (f 1.03, m 0.00, total 0.58);
не одна (not alone) (f 0.00, m 1.35, total 0.58). In this case, we observe the personifi-
cation of біда (misery) (the metaphorical model БІДА – ЦЕ ІСТОТА (MISERY is A
HUMAN BEING). Similarly, навчить (will teach) (f 5.15, m 0.00, total 2.92);
навчить як на світі жить (will teach how to live in the world) (f 1.03, m 0.00, total
0.58); навчає (teaches) (f 0.00, m 1.35, total 0.58); хай не торкнеться (may not touch)
(f 0.00, m 1.35, total 0.58); та й годі (and nothing can be done) (f 1.03, m 0.00, total
0.58).
Moreover, we included in the scenario frame the reactions related to the experience
of the subject of misery in a number of states: сум (sadness) (f 1.03, m 2.70, total 1.75);
тривога (anxiety) (f 1.03, m 0.00, total 0.58); журба (mourning) (f 1.03, m 0.00, total
0.58); жах (horror) (f 1.03, m 0.00, total 0.58); жаль (pity) (f 1.03, m 0.00, total 0.58).
It should be noted that predominantly women responded to the stimulus біда (misery)
in this way.
The responses which belong to the scenario frame related to the actions of the sub-
ject are not frequent: допомогти (to help) (f 0.00, m 1.35, total 0.58), допомога (help)
(f 0.00, m 1.35, total 0.58). Such reactions were received only from male respondents.
The index of mutual associative relation of concepts and sub-concepts is an im-
portant indicator (see Table 2), which is calculated by the ratio of the number of iden-
tical reactions to the total number of reactions received [18]. For comparison, the asso-
ciative relations between the concepts of ENVY and GREED were analyzed.
Figure 4 visualizes the associative distance between the investigated stimuli that ver-
balize the concepts of БІДА (MISERY), ЗАЗДРІСТЬ (ENVY), ЖАДІБНІСТЬ
(GREED).
The index of mutual associative relation between derivatives БІДА (MISERY) and
БІДУВАТИ (BE MSERABLE) is 0.040. The common reactions are: лихо (disaster)
(8), погано (badly) (4), сім’я (family) (2).
Table 2. The index of mutual associative relation of the concepts and sub-concepts
Con- біда біду- бідна бідний горе заздріс заздри заздріс заздрі- жа
cepts/ вати як як ть ти на як с¬ний ді
stim- як бн
uli іст
ь
біда 0
біду- 0.040 0
вати
бідна 0.0657 0.0353 0
як
бідний 0 0.1181 0.573 0
як
горе 0.4425 0.0407 0.0422 0.0088 0
заздрі- 0.1392 0.0592 0.0647 0.0222 0.0182 0
сть
зазд- 0.08 0.1242 0.0063 0.0154 0.1615 0.2140 0
рити
зазд- 0.0067 0.0263 0.1918 0.1204 0.0101 0.1245 0.2601 0
рісна
як
зазд- 0 0.0102 0.2163 0.2491 0.021 0.1027 0.0441 0.3739 0
рісний 83
як
жадіб- 0.1648 0.0667 0.0157 0.0615 0.0994 0.2901 0.2662 0.1206 0.0478 0
ність
To compare, for ЗАЗДРІСТЬ (ENVY) and ЗАЗДРИТИ (BE ENVIOUS) it is 0.2140.
The index of mutual associative relation between бідна як (miserable as (f)) and бідний
як (miserable as (m)) is 0.573. The most frequent common reactions of the respondents
are церковна миша (the church mouse) (68); миша (mouse) (68), бомж (tramp) (27),
жебрак (beggar) (11), кінь (horse) (7), церковна миш (church mouse) (6), собака
(dog) (6), Україна (Ukraine) (4). To compare, for ЗАЗДРІСНА ЯК (ENVIOUS AS
(f)) and ЗАЗДРІСНИЙ ЯК (ENVIOUS AS (m)) it is 0.3740. And, for БІДА (MISERY)
and ГОРЕ (GRIEF) the index of mutual associative relation is 0.4425. The most fre-
quent common response to the stimulus горе (grief) is біда (misery) (32), and con-
versely the most frequent response to the stimulus горе (grief) is біда (misery) (25);
common reactions are (presented in decreasing order of absolute frequency) – смерть
(death) (22), лихо (disaster) (17), сум (sadness) (11), нещастя (misery) (8), погано
(badly) (5), радість (joy) (4), втрата (loss) (4), щастя (happiness) (3), війна (war)
(3), пожежа (fire) (2), не біда (no trouble) (2), в Україні (in Ukraine) (2), велика
(great) (2), жах (horror) (2), журба (grief) (2), лишенько (disaster) (2), навчає
(teaches) (2). To compare, for ЗАЗДІСТЬ (ENVY) and ЖАДІБНІСТЬ (GREED) it is
0.2901. Table 3 presents the descriptive indices of mutual associative relation of the
concepts (IMAR) in descending order.
Fig. 4. Associative distance between the concepts of БІДА (MISERY), ЗАЗДРІСТЬ (ENVY),
ЖАДІБНІСТЬ (GREED)
Table 3. The indices of mutual associative relation of the concepts
The concept IMAR The con- IMAR The con- IMAR е The con- IMAR
of БІДА cept of cept of cept of
(MISERY) БІДУВА БІДНА БІДНИЙ
ТИ (BE ЯК (MI- ЯК
MIS- SERA- (MISER-
ERA- BLE AS ABLE
BLE) (f)) AS (m))
горе 0.4425 заздрити 0.1242 бідний 0.573 бідна як 0.573
як
жадібність 0.1648 бідний 0.1181 заздріс- 0.2163 заздріс- 0.2491
як ний як ний як
заздрість 0.1392 жадіб- 0.0667 заздріс- 0.1918 заздрісн 0.1204
ність на як а як
заздрити 0.08 заздрість 0.0592 біда 0.0657 бідувати 0.1181
бідна як 0.0657 горе 0.0407 заздрість 0.0647 жадіб- 0.0615
ність
бідувати 0.040 біда 0.040 горе 0.0422 заздрість 0.0222
заздрісна як 0,0067 бідна як 0,0353 бідувати 0,0353 заздрити 0,0154
бідний як 0 заздріс- 0.0263 жадіб- 0.0157 горе 0.0088
на як ність
заздрісний 0 заздріс- 0.0102 заздрити 0.0063 біда 0
як ний як
We can notice higher IMAR for the concepts that are verbalized by units belonging to
one part of speech, for example: for бідувати (to be miserable) and заздрість (envy)
IMAR is 0.1242, while for misery and to be miserable it is only 0.040. The highest
IMAR is typical of synonyms, for example: for БІДА (MISERY) and ГОРЕ (GRIEF)
it is 0.4425. Figure 5 shows reactions to stimuli БІДА (MISERY) and ГОРЕ (GRIEF)
and presents the visualization of associative reactions based on the weight of each ver-
tex.
Fig. 5. The responses to the stimuli БІДА (MISERY) and ГОРЕ (GRIEF)
Semantic distance between the words is determined by analyzing distribution. This
method is applied to Word2Vec Models trained on Wikipedia. It should be noted that
Wikipedia texts belong to scientific and popular scientific styles and only partially re-
flect the discourse of a particular linguistic community. Obviously, the best option
would be to train the tool using the corpus. However, also in this case we observe a
certain coincidence of results in the corresponding frames. Top 10 similar words or
synonyms for біда (misery) are as follows: рідня (relatives) 0.701118, страшна (hor-
rible) 0.685616, донечка (daughter) 0.684960, старенька (old lady) 0.676980, твоя
(your) 0.673573, тиша (silence) 0.672945, недуга (sickness) 0.667534, люба (darling)
0.663111, завірюха (whirlwind) 0.657884, відьма (witch) 0.652087. See also Figure
6, which shows top 30 analogous words or synonyms for БІДА (MISERY). We can
observe more coincidence of the results of our associative test with the results obtained
with the help of the Word2Vec Models tool for stimulus заздрість (envy). Top 10
similar words or synonyms for заздрість (envy) are: жадібність (greed) 0.843240,
ревнощі (jealousy) 0.772056, ненависть (hatred) 0.766005, марнославство (vanity)
0.754607, гнів (anger) 0.749902, злість (anger) 0.749735, зарозумілість (arro-
gance) 0.745534, хтивість (lust) 0.736004, лицемірство (hypocrisy) 0.718854. See
Figure 7, which shows top 30 analogous words or synonyms for ЗАЗДРІСТЬ (ENVY).
The associative test data and the corpus data are extremely valuable for compiling
dictionaries. For example, The Dictionary of the Ukrainian Language (СУМ-20) pro-
vides the following definition (omitting illustrative material): БІДА (MISERY), і́, f. 1.
An accident; a nasty incident that causes suffering; misfortune, evil. // Hardships, trou-
ble. // Bad feeling, misfortune. 2. Guilt, harm. The results of the associative test show
that the synonym горе (grief) is more frequent than лихо (disaster), the latter is used in
the definition. In addition, the corpus data should be used to determine collocations and
enter the most typical ones into the dictionary.
Fig. 6. Top 30 analogous words or synonyms for БІДА (MISERY)
Fig. 7. Top 30 analogous words or synonyms for ЗАЗДРІСТЬ (ENVY)
4 CONCLUSIONS
The associative test was aimed, first, at obtaining statistical and quantitative data nec-
essary for modeling the conceptual domain БІДА (MISERY) and establishing the areas
of its intersection with related concepts in terms of the typology of associative relations;
second, at revealing the mechanisms of cognitive modeling of the corresponding
frames, which reflect the cognitive structure, individual and collective experience of
Ukrainians, their values and cultural associations.
Determining the associative distance between the concepts through the reconstruc-
tion of data on their mutual associations (the index of mutual associative relation), as
well as visualization of the results of associative test conducted by Ukrainian internet
users, made it possible to identify typologically common and distinct plots within the
obtained associative verbal network of the conceptual domain БІДА (MISERY) (based
on the semantic and statistical relevance of each of the vertices represented in the
graphs).
Contrastive analysis of collocations and the frequency of metaphorization of word
combinations in the text corpora (in particular the GRAC corpus) allowed us, first, to
identify associative statistical patterns of their modeling by means of the latest quanti-
tative, cognitive and ethnosemiotic methods; second, to describe the taxonomy of the
frames (descriptive, scripted, axiological, parametric, possessive, etc.); and, third, ap-
plying Mutual Information score, etc. to find out the ranges of intersection, gradations,
oppositions (synonymous and antonymic paradigmatic correlates), areas of relative and
absolute frequency, typicality, uniqueness, usability, casualness, gender markedness of
the responses to the stimulus БІДА (MISERY).
By establishing the index of mutual attraction and repulsion of the associations
within the common AVN (adjacent conceptual domains where we observe the ‘reci-
procity and derivability of concepts’ / and or sub-concepts), the most frequent (abso-
lute) reactions have been presented in ascending and descending order by gender and
axiological characteristics. Conclusions have been made based on the statistical typo-
logical analysis of comparative phrases, phraseological, socio - and emotionally evalu-
ative responses, mostly semiotically and epidigmatically marked, connected with the
vital and family values (LIFE-DEATH, HAPPY, HAPPYNESS, HEALTH, FAMILY,
COUNTRY), anthropomorphic metaphors (the metaphorical model БІДА (MISERY)
is A HUMAN BEING), stereotypical and prescriptive associations. The in-depth qual-
itative analysis in terms of interframe merging (the reconstruction of syntagmatic con-
nections with action predicates) made it possible to establish the following areas of
respondents' conceptualization: threat, danger, natural disaster, technogenic catastrophe
and other destructive forces. This, in turn, made it possible to visualize the associative
distance between the stimulus words. It has been revealed that the responses of female
respondents, naturally, were closer connected with various fragments of negative expe-
rience and internal state of the person, her worries, unlike male reactions, which are
mostly reactions related to the concept of COOPERATION (assistance, support in dif-
ficult situations).
The conducted associative test (which provides the obtained associative reactions
on the basis of weight, relevance of each vertex) gives grounds to argue that higher
IMAR is typical of the concepts represented by words belonging to one part of speech
or synonyms and it is the lowest in case of derivative responses of respondents, as in
БІДА (MISERY) and БІДУВАТИ (BE MISERABLE).
The methodology of determining the semantic distance between words based on the
Word2Vec Models allowed us to observe the peculiar isomorphism of adjoining frames
and their conceptual correlation within the stimuli БІДА (MISERY) and ГОРЕ
(GRIEF) taking into account the qualitative-quantitative correlation with typical reac-
tions to the stimulus ЗАЗДРІСТЬ (ENVY) and its synonyms – ЖАДІБНІСТЬ
(GREED), ХТИВІСТЬ (LUST), РЕВНИВІСТЬ (JEALOUSY), etc.
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