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The System for Automatic Stylometric Analysis of Ukrainian Media Texts TextAttributor 1.0 (Techniques, Means, Functionality)

Abstract

This paper presents the structure, algorithms, implementation, and experimental results of the automatic TextAttributor system developed by the authors of the paper for statistical Ukrainian-language text parameterisation using a multiparametric set of statistical indices, characterising the author’s text style and applicable to authorship attribution tasks. Based on the created linguistic resources and software, the system generates a linguistic analysis based on the calculated statistical indices and performs a comparative study of two texts. An additional criterion for statistical indexing is the text toxicity index, calculated through the method of verbal identification of toxic sentiment. Authorship and toxicity detection tasks are addressed using two methods: dictionary- and rule-based statistical calculations and machine learning. The current findings implemented in the beta version of TextAttributor are thoroughly examined.

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The System for Automatic Stylometric Analysis of Ukrainian Media Texts TextAttributor 1.0 (Techniques, Means, Functionality)

Author: Nataliia Darchuk; Oksana Zuban; Valentyna Robeiko; Yuliia Tsyhvintseva; Victor Sorokin; Mykola Sazhok
Year: 2024
DOI: 10.35321/all91-09
Source: https://journals.lki.lt/actalinguisticalithuanica/article/download/2328/2430
 S aipsniai / A icles 223
NATALIIADARCHUK
Ta asShe chenkoNa ionalUni e si yo Kyi
ORCIDid:o cid.o g/0000-0001-8932-9301
Fieldso  esea ch:compu e linguis ics,co puslinguis ics,
quan i a i elinguis ics,g amma andseman icso  he
Uk ainianlanguage.
OKSANAZUBAN
Ta asShe chenkoNa ionalUni e si yo Kyi
ORCIDid:o cid.o g/0000-0002-2644-3892
Fieldso  esea ch:compu e linguis ics,linguis icexpe ise,
quan i a i elinguis ics,g amma andseman icso  he
Uk ainianlanguage.
VALENTYNAROBEIKO
Ta asShe chenkoNa ionalUni e si yo Kyi
ORCIDid:o cid.o g/0000-0003-2266-7650
Fieldso  esea ch:speechanalysis, ecogni ionand
syn hesis,phone ics,na u allanguagep ocessing.
YULIIATSYHVINTSEVA
Ta asShe chenkoNa ionalUni e si yo Kyi ,
Ins i u eo  heUk ainianLanguageo  heNa ional
Academyo Scienceso Uk aine
ORCIDid:o cid.o g/0000-0002-9684-3840
Fieldso  esea ch:Uk ainianneology,lexicologyand
lexicog aphy.
VICTORSOROKIN
Ta asShe chenkoNa ionalUni e si yo Kyi
ORCIDid:o cid.o g/0000-0002-3637-0535
Fieldso  esea ch:au oma icsyn axanalysis,au oma ic
seman icanalysis,na u allanguagep ocessing.
NATALIIA DARCHUK, OKSANA ZUBAN, VALENTYNA ROBEIKO,
YULIIA TSYHVINTSEVA, VICTOR SOROKIN, MYKOLA SAZHOK
224 Ac aLinguis icaLi huanicaXCI
MYKOLASAZHOK
Ins i u e o in o ma ion echnologiesandsys ems
o  heNa ionalAcademyo Scienceso Uk aine
ORCIDid:o cid.o g/0000-0003-1169-6851
Fieldso  esea ch:speechanalysis, ecogni ionand
syn hesis,na u allanguagep ocessing.
DOI:doi.o g/10.35321/all91-09
THESYSTEMFORAUTOMATIC
STYLOMETRICANALYSIS
OFUKRAINIANMEDIA
TEXTSTEXTATTRIBUTOR1.0
(TECHNIQUES,MEANS,
FUNCTIONALITY)
Uk ainosžiniasklaidos eks ųau oma inės
s ilome inėsanalizėssis ema„Tex A ibu o 1.0“
(me odai,p iemonės, unkcionalumas)
ANNOTATION
Thispape p esen s hes uc u e,algo i hms,implemen a ion,andexpe imen al esul s
o  heau oma icTex A ibu o sys emde elopedby heau ho so  hepape  o s a is ical
Uk ainian-language ex pa ame e isa ionusingamul ipa ame icse o s a is icalindices,
cha ac e ising heau ho ’s ex s yleandapplicable oau ho shipa ibu ion asks.Based
on hec ea edlinguis ic esou cesandso wa e, hesys emgene a esalinguis icanalysis
basedon hecalcula eds a is icalindicesandpe o msacompa a i es udyo  wo ex s.An
addi ionalc i e ion o s a is icalindexingis he ex  oxici yindex,calcula ed h ough he
me hodo  e baliden i ica iono  oxicsen imen .Au ho shipand oxici yde ec ion asks
a eadd essedusing wome hods:dic iona y-and ule-baseds a is icalcalcula ionsand
machinelea ning.Thecu en  indingsimplemen edin hebe a e siono Tex A ibu o 
a e ho oughlyexamined.
 KEYWORDS: Compu a ionallinguis ics,Uk ainianlanguage,sen imen analysis,
au ho shipa ibu ion,s ylome y, ex classi ica ion.
 S aipsniai / A icles 225
The Sys em o Au oma ic S ylome ic Analysis
o Uk ainian Media Tex s Tex A ibu o 1.0
(Techniques, Means, Func ionali y)
ANOTACIJA
Šiame s aipsnyje p is a oma s aipsnio au o ių suku os au oma inės sis emos
„Tex A ibu o “,ski oss a is iniamuk ainiečiųkalbos eks ųpa ame iza imuinaudojan 
daugiapa ame inįs a is inių odiklių inkinį,apibūdinan įau o iaus eks os iliųi  aikomą
au o ys ės a ibucijos užda iniams, s uk ū a, algo i mai, įdiegimas i  ekspe imen iniai
ezul a ai.Suku ųling is iniųiš ekliųi p og aminėsį angospag indusis emagene uoja
ling is inęanalizępagalapskaičiuo uss a is iniusindeksusi a liekad iejų eks ųlyginamąją
analizę.Papildomass a is inioindeksa imok i e ijusy aneigiamasnuo aikassukeliančio
eks o indeksas, apskaičiuojamas aikan  žodinio neigiamų nuo aikų iden i ika imo
me odą.Au o ys ėsi pagiežosnus a ymoužduo yssp endžiamosd iemme odais:žodynu
i  aisyklėmis pag įs ais s a is iniais skaičia imais i  mašininiu mokymusi. Daba iniai
ezul a ai,gau inaudojan is„Tex A ibu o “be a e sija,išsamiaiišnag inė i.
 ESMINIAIŽODŽIAI:kompiu e inėling is ika,uk ainiečiųkalba,jausmingumoanalizė,
au o ys ėsp isky imas,s ilome ija, eks oklasi ika imas.
1. INTRODUCTION
Tex ological esea chgainednewscien i icimpo ancewi h head ancemen 
o compu a ionallinguis icsme hods,whichcon ibu ed o he o ma iono a
newdi ec ion ha canbeconside eddigi al ex ology.Wi hin hiseme ging
discipline,weconcep ualizedigi al ex ologyasha nessingau oma edco pus
linguis ics echniques,coupledwi hma hema icalmodels o quan i a i e ex 
analysis.Guidedby hecu en  askso mode nquan i a i elinguis icsand
na u allanguagep ocessing,ou  eamhasde elopedasys em o au oma ic
linguis ic-s a is ical analysis o  media ex s, which has been implemen ed
as a web applica ion named Tex A ibu o  (Tex A ibu o  1.0 2024). The
sys emope a esin ou  asks:1)s a is ical ex pa ame e iza ion;2)s ylome y:
de e mining he linguis ic-s a is ical ea u es o  idiolec ; 3) a ibu ion:
de e mining hedeg eeo simila i ybe ween ex s;and4)sen imen analysis:
iden i ying nega i e sen imen  lexicon in ex s. Addi ionally, wi hin he
sys em, wo linguis ic expe  conclusions a e au oma ically gene a ed based
on he esul so  hesecondand ou h asks.Themul i unc ionali yo  he
Tex A ibu o sys em equi esuse s o amilia ize hemsel eswi hi sope a ing
p inciples.Thepu poseo  hisa icleis oacquain  heacademicandeduca ional
philologicalcommuni ywi h hesys em’sc ea ionme hodology,a chi ec u e,
and ope a ional esul s o p o ide a clea  unde s anding o  i s unc ions
and analy ical capabili ies, which a e pa icula ly ele an . This app oach is
especially ele an  o analyzingla ge olumeso in e ne communica ionsand
NATALIIA DARCHUK, OKSANA ZUBAN, VALENTYNA ROBEIKO,
YULIIA TSYHVINTSEVA, VICTOR SOROKIN, MYKOLA SAZHOK
226 Ac aLinguis icaLi huanicaXCI
enhancingin o ma ionde ences a egiesdu ing heongoingRussian-Uk ainian
wa .Theconcep o de eloping anau oma icsys emo Uk ainian-language
ex a ibu iona ose om heanalysiso  esea chin he ieldo Uk ainian
co puslinguis ics(Da čuk 2013)ands a is icals udieso  heau ho ’s s yle
(Da čuke al.2021;Da chuk,So okin2022;Zuban’2019)conduc edusing he
oolso  heUk ainianLanguageCo pus(KUM)by hep ojec au ho s.
Du ing he de elopmen  o  he Tex A ibu o  sys em, he ollowing
me hodswe eemployed:componen analysis,dis ibu i eanalysis,andcon en 
analysis.Con en analysis,aquan i a i eandquali a i eme hod o ex ac ing
in o ma ion om ex , u ilized na u al language p ocessing and s a is ical
echniques.Quan iza ionandsen imen analysiswe ealsoapplied.Sen imen 
analysis au oma ically iden i ies ex  onali y based on bo h he emo ional
colou ingand heau ho ’sassessmen o e en so objec s,whichwasachie ed
u ilizingdic iona y-and ule-baseds a is icalcalcula ions.
Addi ionally, machine lea ning me hods, including deep lea ning, we e
inco po a ed.Thes a is icals uc u eo a ex unde s oodasi squan i a i e
model,enables heiden i ica iono i s unc ionals yle,au ho ship,andpe iod
o c ea ion.In hiswo k, hes a is icals uc u ecomponen swe eex ac edby
analyzinglexicalandg amma icals a is ical ea u esusingindexing echniques
andEuclideandis anceme ics.TheEuclideandis ance,whichmeasu es he
dis ancebe ween wopoin sinann-dimensionalEuclideanspace,isoneo  he
mos widelyusedme icsinlinguos a is ics o clus e analysisins ylome y
andau ho shipa ibu ion.
The no el y o  he esul s is he i s  implemen a ion in compu a ional
linguis ics o  an au oma ed mo pho-syn ac ic-seman ic s ylome ic model
o  ex  analysis, based on 15 s a is ical indices ha  p ima ily pa ame e ize
hemo phological,aswellassyn ac icandseman ics uc u eo  he ex .A
s ylome icmodelisase o s a is icalpa ame e so a ex (lexical,mo phological,
syn ac ic,e c.),basedonwhichacompa a i eanalysiso  his ex isca ied
ou wi h hes ylome icmodelo  he unc ionals yle.Inou opinion,i is
possible o ob ain a s ic , de e minis ic, scien i ically g ounded sys em o 
commonanddis inc i e ea u esins yles,gen es,e c.byusings a icme hods
in hecons uc iono as ylome icmodel.Fo  he i s  ime, hes ylome ic
modelin oduces he oxici yindexpa ame e ,whichcha ac e is icallyde ines
media ex sdu ing heRussian-Uk ainianwa .Thismodelisimplemen edno 
onlyin he unc iono s a is icalpa ame e iza iono  ex s,whichis ypical
o sys emso  his ype,bu alsoin he unc iono compa ing heanalyzed
ex wi h hemedias yleo  heUk ainianlanguage,and o s ylome icand
a ibu ion asks in ol ing wo o  mo e ex s. The heo e ical signi icance
ex ends o he alida ion o  wo me hods o  de e mining ex  oxici y and
 S aipsniai / A icles 227
The Sys em o Au oma ic S ylome ic Analysis
o Uk ainian Media Tex s Tex A ibu o 1.0
(Techniques, Means, Func ionali y)
au ho shipinUk ainian:1) h oughdic iona yand ule-basedapp oaches,and
2) iamachinelea ning,includingdeeplea ning.
2. RELATEDWORKS
Inmode nUk ainianlinguis ics,subs an iallinguis ic-s a is icals udiesha e
beenconduc edon heidiolec so Uk ainianw i e sandpoe s,includingTa as
She chenko, Lesya Uk ainka, Vasyl S us (Zuban’ 2019), I an F anko (Buk
2021),RomanI anychuk(Lo o ska2022),Vale iiShe chuk(Volos,Le chenko
2023), Ma iia Ma ios, Yu ii And ukho ych, Oksana Zabuzhko (Ka aso ,
Le chenko 2024), I an D ach, Mykola Ving ano sky (Da chuk e al. 2024),
LinaKos enko(Zuban’2019;Da chuke al.2024),amongo he s.Theses udies
we econduc edon ep esen a i e ex samples(long ex s)usingp edominan ly
oneo a ew(nomo e han i e)s a is icalpa ame e s,o enwi hou applying
s ylome iccompa ison.Fu he mo e,due o helabo iousna u eo conduc ing
linguis ic-s a is icalexpe imen s,Uk ainianlinguis icshasla gelyo e looked
comp ehensi es a is icalpa ame e iza ion,compa isono analyzed ex swi h
s anda ds a is icalpa ame e so  unc ionals yles,de e mina iono  hedeg ee
o  ex simila i y,aswellass ylome icanda ibu ionanalysiso sho  ex s.
Theuseo  heTex A ibu o sys eminlinguis ic-s a is ical esea ch,aimed
a  pe o ming hese asks au oma ically, will no  only p o ide equency
cha ac e is ics o  linguis ic phenomena bu  also enable e icien  s ylome ic
analysis esul inginanexpe opinion.
The Tex A ibu o  sys em has ad an ages compa ed o i s coun e pa s
inglobalscience.Mos exis ingsys emsandmodelsalso ocuson heuseo 
indi iduallinguis ic-s a is icalmodules oiden i yoneo a ew,mos ly o mal
(n-g ams,mos  equen wo ds,le e s), ex pa ame e s(Ede 2015;Canhasie al.
2022;LIWC-22;Khomy skae al.2023;ALIAS).Incon as ,Tex A ibu o 1.0
o e sacomp ehensi eapp oach,includingin e ac i es a is icalanalysiso  he
lexical,mo phological,syn ac ic,andseman ics uc u eo  he ex in eal- ime
ac oss15pa ame e s.
A ibu ion o  ex s is ac i ely de eloped in o eign ex ual s udies, in
pa icula , Bu ows’sme hod(Bu ows2002; A gamon2007;Ede ,Rybicki
2013; Bu ows e al. 2014) e ec i eness is es ed in many s udies on la ge
olumeso  ex ualda ao  a iouss yleslike:Englishp oseo  heea ly20 h
cen u y(Hoo e 2004);mode nEnglishpoe y(Hoo e 2005);poe icwo ks
inLa in(Rybicki,Ede 2011);p osewo kso majo gen esinEnglish,F ench,
I alian,Ge man,Polish,Hunga ian,aswellasLa inandA abic(Rybicki,Ede 
2011;E e e al.2015;Jannidise al.2015);poli ical ex sinEnglish,including

NATALIIA DARCHUK, OKSANA ZUBAN, VALENTYNA ROBEIKO,
YULIIA TSYHVINTSEVA, VICTOR SOROKIN, MYKOLA SAZHOK
228 Ac aLinguis icaLi huanicaXCI
hea ibu iono speecheso Ame icanp esiden s(Sa oy2015).Onemo e
au oma ed linguis ic analysis me hod called “Linguis ic Inqui y and Wo d
Coun ”(LIWC)isimplemen edasacomme cialapplica ionandadap ed o
se e allanguages(Meie e al.2019;LIWC-22).
In ecen yea s, he askso au oma ic ex a ibu ionha ep edominan ly
usedei he  ule-baseds ylome icme hodso deeplea ningme hods(Ede 
2015;Canhasie al.2022).Bo hme hodswe eimplemen edin heTex A ibu o 
sys em,e ec i ely unc ioningbu yieldingdi e en ou comes:1)The ule-
basedme hodallowsau oma ing hegene a iono linguis icconclusionsabou 
idiolec and ex  oxici y;2)Themachinelea ningme hodde e minesonly he
deg eeo  oxici yand hesimila i yo  ex sandcanbeusedinclassi ica ion
asks o moni o ing ex ualcon en .
The ecen  machine lea ning me hods o  sen imen  analysis and ex 
au ho shipiden i ica iona ebasedons a is icalapp oaches(TF-IDF,La en 
Di ichle Alloca ion)anddeeplea ning echniqueswi h a iousa chi ec u es
(CNN,LSTM,BERT)incombina ionwi hs ylome icme hods(Gup ae al.
2019;Canhasie al.2022;Bone ie al.2023).The epo ed esul sa eex emely
dependen on henumbe o classes( ypeso  oxici y,au ho s),gen e,leng h
o  he ex and,mos impo an ly, he olumeo  hep ope lyanno a ed ex 
co pusused o  he ainingp ocedu e.Thus,highaccu acy a esin he asks
o de ec ing oxici yandha espeechexceed90%usingaco puscon aining
enso  housandso documen s(Alkomah,Ma2022).Fo example,mo e han
90%accu acyinau ho shipa ibu ionisachie ed o English-languageli e a y
wo ksac oss1000au ho s,usingaco puso 6000documen s o 15au ho s.In
u n, o co po acon ainingless han1500documen s he epo edaccu acy
isabou 70%(Khane al.2023).Fo  heUk ainianlanguage, ex au ho ship
iden i ica ion and sen imen / oxici y analysis a e unde s udied p oblems
(Lupeie al.2020),mo eo e ,suchsys emsdono p oducelinguis icexpe ise
andcanno beusedas ools o linguis ic esea ch.
3. GENERALCHARACTERISTICSOFTHE
TEXTATTRIBUTORSYSTEMOPERATING
Du ing he de elopmen  o  Tex A ibu o , he ollowing asks we e
accomplished:1)Theo e icalLinguis ics:Ame hodologywasde eloped o 
o malizedmo phological,s a is ical,s ylome ic,a ibu ional,andsen imen 
analyses;2)So wa eEnginee ing:Thes uc u eo linguis icda abasesand
he so wa e o  he a o emen ioned au oma ic analyses we e de eloped;
3)Expe imen alLinguis ics:Thesys emwas es edonUk ainianmedia ex s,and
 S aipsniai / A icles 229
The Sys em o Au oma ic S ylome ic Analysis
o Uk ainian Media Tex s Tex A ibu o 1.0
(Techniques, Means, Func ionali y)
ananaly icalmodule o au oma ics ylome icexamina ionwasimplemen ed.
Theau oma edlinguis icsys em,implemen edasawebapplica ion,p ocesses
use -en e ed media-s yle ex s, gene a ing nume ical alues o  s a is ical
pa ame e s ha cha ac e ize he ex ’sa ibu es.Thesys em ollowsas uc u ed
ope a ionsequence:
1.Tex Tokeniza ion:B eakingdown he ex in osen encesandwo ds o 
analysis.
2.Mo phological Labeling: Assigning labels o wo ds based on hei 
g amma ical o ms.
3.Con ex ual Analysis: Upda ing he mo phological labels conce ning
con ex .
4.Syn ac ic Analysis:Es ablishingbina y ela ionshipsbe weenwo dsin
sen ences ounde s and hei g amma icals uc u e.
5.Syn ac ic Rela ion Es ablishmen :De e miningsyn ac icconnec ions
basedonp ede ined ules.
6.Emo ionally Nega i e Vocabula y Ma ching:Iden i yingwo ds oma
p ede inedse o nega i e ocabula y.
7.S a is ical Pa ame e E alua ion:Assessings a is icalpa ame e s o  he
inpu  ex usingau oma icallycompiled equency ocabula ies.
8.Visualiza ion o Resul s:P esen ings a is icalpa ame e iza ionou comes
g aphically,wi hempi ical aluesandcon idencein e als.
9.Compa ison o Resul s:Visualizings a is icalpa ame e iza ionou comes
o  womedia-s yle ex s, acili a ingcompa ison.
10.Euclidean Dis ance E alua ion:Quan i ying hedissimila i ybe ween
womedia-s yle ex s.
11.Expe Opinion Gene a ion:Gene a ing woexpe opinions:oneon
ex a ibu ionandano he on ex  oxici y h oughlinguis icexamina ion.
12.Toxici y De ec ion and Au ho ship Iden i ica ion:Le e agingmachine
lea ning echniques, pa icula ly neu al ne wo k models, o  de ec ing
oxici yandiden i yingau ho s.
The esul s o  he sys em a e o ganized in he ollowing pa i ions: Tex 
A ibu ion Index G oup, Tex  A ibu ion Expe  Opinion, Compa ison o 
Tex A ibu ion,Linguis icExpe iseo Tex Toxici y,andNeu alNe wo k
Opinions.
In Tex A ibu ion Index G oup (Fig. 1), s a is ical pa ame e s a e
o ganizedbasedon heinpu  ex :column1displays heIndex i le,column
2p esen s heempi icalnume ic alue,andcolumn3p o idesa isual e e ence
by compa ing he empi ical alue o  he index wi h con idence in e al
NATALIIA DARCHUK, OKSANA ZUBAN, VALENTYNA ROBEIKO,
YULIIA TSYHVINTSEVA, VICTOR SOROKIN, MYKOLA SAZHOK
230 Ac aLinguis icaLi huanicaXCI
h esholds(lowe anduppe )de i ed omUk ainianmedias yle ex s.The
empi icalnume ic alueis ep esen edon hescalebya illedin e ed iangle.
FIGURE 1:A agmen o  he ex a ibu ion esul
In Tex A ibu ion Expe Opinion (Fig. 2), we p esen  conclusions
ega ding he ypicalo indi iduallinguis ics a is ical ea u esex ac ed om
heanalyzed ex  o eaches ima edindex.Theseconclusionsa ede i ed om
answe s o he ques ion: Does henume ical alue o  he index allwi hin
hecon idencein e alo  hemedias yleo  heUk ainianlanguage?Based
onacompa isono nume ical alueswi h h eshold alueso  hecon idence
in e al, hesys emgene a es h eepossibleanswe s( ypicalsignso media
s yle,signso idios ylelowe  hanno malmedias yle,andsignso idios yle
highe  hanno malmedias yle).
In Compa ison o Tex A ibu ion (Fig. 4, subsec ion 4.2), upon
selec ing“Calcula eVec o Dis ance”, abula edda aisp omp lyupda edas
ollows:Column1lis suse -en e ed ex salongwi h hep e iouslyanalyzed
ex ; Column 2 displays he numbe  o  sen ences in each ex ; Column
3shows hewo dcoun ;Column4p esen s heEuclideandis ancebe ween
heanalyzed ex andeach ex in he able;Column5,labelled“Compa e”,
ini ia esanau oma iccompa isono s a is icalindicesbe ween heanalyzed ex 
and heselec ed ex .Uponac i a ing heco esponding“Compa e”elemen ,
comp ehensi ein o ma ionon hes a is icalcompa isonbe ween wo ex sis
p o idedin he“Tex A ibu ionIndices”g oup(Fig.3).
 S aipsniai / A icles 231
The Sys em o Au oma ic S ylome ic Analysis
o Uk ainian Media Tex s Tex A ibu o 1.0
(Techniques, Means, Func ionali y)
FIGURE 2: Anexampleo gene a edexpe opinion
In Linguis ic Expe ise o Tex Toxici y (subsec ion 4.3), a lexical-
seman icin e p e a iono  hecalcula ed oxici yindexisp esen ed(Fig.6).
InNeu al Ne wo k Opinionswep esen  heou pu o ou deeplea ning
model,whichquan i ies ex  oxici yonascale om0(non- oxic) o1(high
oxici y).Wealsoassess ex simila i y oknownau ho s,wi h alues anging
om0(nosimila i y) o1(highsimila i y),basedon heau ho s hemodelwas
ainedon.Resul sa eshownonly o  es swi hasimila i ymeasu eexceeding
0.1.Ou cu en sys emope a esindemomode,u ilizingalimi edco puso 
au ho  ex s ogaugesimila i ywi huse -en e ed ex .
4. ATTRIBUTIONOFUKRAINIAN-
LANGUAGETEXTS:EXPERIMENTS,
RESULTSANDDISCUSSIONS
4.1. S a is icalPa ame e iza ionIndices
Thede elopeds ylome icmodelsol es wo asks:
1)Iden i yingindi idual ea u eso anau ho ’ss yle(s ylome y);
2)Assessing hesimila i ybe ween wo ex sbasedonlinguis icands a is ical
pa ame e s(a ibu ion).
NATALIIA DARCHUK, OKSANA ZUBAN, VALENTYNA ROBEIKO,
YULIIA TSYHVINTSEVA, VICTOR SOROKIN, MYKOLA SAZHOK
238 Ac aLinguis icaLi huanicaXCI
Today, he in o ma ion componen  has become pa icula ly impo an  in
hyb idwa a e.The e o e, hema e ialo ou s udywasa esea chco puso 
onlinemedia ex so poli icaldiscou sewi ha olumeo 10millionwo ds.
Weuse he e m“ oxic ex ”inab oadsense.These ex sa echa ac e izedby
ha assmen , h ea s,obsceni y,cybe -bullying, olling,andiden i y-basedha e
ex s,andcon ainemo iogens,whicha ephenomenaandobjec s ha cause
nega i eemo ionsinape son(e.g.wa ,ai aid,co up ion).
Thisp ojec aimed ode e mine hepo en ial o  he ealiza iono nega i e
sen imen inUk ainian ex sand ode elopanau oma edsys em o iden i ying
oxiccon en .This askcomp ised woconsecu i esub asks: i s ,de eloping
asys emo  oxic ex linguis icexamina ionwi hde e mina iono  he oxici y
indices h oughdic iona yanalysisand ule-basedme hods;second,cons uc ing
a aining da ase  o  machine lea ning pu poses and he de elopmen  o  a
neu alne wo k o p edic ing ex  oxici yindices.
Le uslooka  hecomple iono  he i s  ask.Thisin ol ed hecons uc ion
o alexicog aphicda abasehousing h eedis inc dic iona ies:
1)Emo iogendic iona y:Acompila iono 5000wo ds(acco ding o he
meaningso lexical-seman ic a ian s)wi hnega i esen imen  ones, a edon
ascaleo –2.Examplesincludeimmo al,impuni y,b ibe yands eal;
2) Ha e Speech Dic iona y: Comp ising 3000 wo ds, including names o 
indi iduals(1620),obscene e ms(613),andabusi elanguage(787).Examples
includewes e ne (западенець: ade oga o yname o people om hewes e n
egionso Uk aine)andhucks e ;
3) Toxic Ph ases: A collec ion o  1500 idioma ic exp essions con eying
nega i eemo ions.Examplesincludeg imaces like a monkey,kisses his a seand
opens his mou h.
Eachen yin heselis swasanno a edwi hseman ic ea u es,wi h heHa e
SpeechDic iona yha ing18 ea u esand heToxicPh aseslis ha ing26.Fo 
ins ance,wo dsin heHa eSpeechDic iona ywe e aggedwi hcha ac e is ics
like‘s’ o sexism,‘ ’ o  acism,and‘e’ o ageism.Thislexicog aphicda abase,
amul ipa ame icsys em,assignsseman ic ea u es ouni s(wo dso ph ases)
which,combinedwi h equencyda a omanalyzed ex ,allows o  oxici y
analysis.
The oxici yindexo  he ex iscompu edusing he o mula:
I ox = (e + |K| (m + )) / n * 10,
He e,nis he ex  olume;eis hecoun o emo ionalwo ds;mis hecoun 
o ha espeechwo ds; is hecoun o  oxicph ases;Kisacoe icien equal
o–2,i emphasisesha espeechwo dsand oxicph ases,whichonascaleo 

 S aipsniai / A icles 239
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o Uk ainian Media Tex s Tex A ibu o 1.0
(Techniques, Means, Func ionali y)
i edigi s(+2,+1,0,–1,–2)co esponds o–2.Index alues a y om0 o
+1.
Fo ins ance, he oxici yindexo  he ex “Peoplewi ha edpen(Людиз
червоноюручкою)”(12sen ences,129wo ds)is1.01,indica ingi shigh oxici y,
as he h eshold o suchsho  ex s anges om0.1 o0.7.Simul aneously,
hesys emgene a es he esul so anau oma iclinguis icexamina iono  he
ex  oxici y( e e  oFig.6),comp ising:1)as a is icalmapo  heseman ic
classeso  he nega i e ocabula yacco ding o heclassi ica ionma ke s o 
lexicog aphiclis s(emo iogens–5, ulga isms–2,sexism–2);2)a ex wi h
speci icwo dso nega i esen imen , e balizing heca ego ieso  hes a is ical
map.Le us akealooka anexce p o  heanalyzed eal-li e ex (Fig.6): hose
people who walk a ound wi h a ed pen and co ec mis akes in o he people’s
pos s: who e en a e you? Do you ha e any idea how annoying you a e? I s udy you
p o iles on pu pose, I’m cu ious abou he wo ld you exis in. This wo ld sca es me
a lo . I since ely hope ha in eal li e we will no c oss pa hs unde any ci cums ances.
(оці люди, які ходять з червоною ручкою і виправляють помилки в чужих
постах: ви хто взагалі такі? Ви хоч уявляеєте, як ви бісите? Я спеціально
вивчаю ваші профілі, мені цікаво в якому світі ви існуєте. Мене цей світ дуже
лякає. Щиро сподіваюся, що в реальному житті ми з вами не пересічемося
ні за яких обставин). He e, hesys emau oma icallyhighligh sinbold he
ollowingwo dswi hanega i ecomponen :mis akes (помилки), o he people’s
(чужих), annoying (бісите), sca es (лякає).
FIGURE6: A agmen o  ex  oxici yau oma edlinguis icexamina ion
NATALIIA DARCHUK, OKSANA ZUBAN, VALENTYNA ROBEIKO,
YULIIA TSYHVINTSEVA, VICTOR SOROKIN, MYKOLA SAZHOK
240 Ac aLinguis icaLi huanicaXCI
5. MACHINELEARNINGAPPROACHES:
EXPERIMENTS,RESULTSAND
DISCUSSIONS
Le us ocuson hesecondope a ionmodeo  heTex A ibu o sys em
dedica ed omachinelea ning echniques.A  heinpu  o model aining,we
ha e ex co po alabelledacco ding o hegoalo eachsub ask:(a) oxici y
de ec ion ex in o ma ionand(b) au ho ship iden i ica ion. Eachco pusis
di idedin o ainingandcon olse s,aswellas, o su icien lyla geco pus,
a alida ion se . The pa ame e s o  he chosen p oblem-sol ing model a e
es ima edon he ainingse .Hype pa ame e so  hemodela eadjus edby he
alida ionse .The inalpe o manceindica o so  hemodela emeasu edona
con olse , akingin oaccoun  hea ailabili yo compu ing esou ces,which
a enecessa y o  hemodel’sope abili y.Aco pus o eachsub askhasbeen
de elopedinpa allelwi h heTex A ibu o machinelea ningcomponen ,so
hecu en modelswe e ainedon ela i elysmallda aincludingsho In e ne 
ex so Uk ainian-languageblogs,commen s,a icles,e c.
5.1. Toxici yde ec ion
Asa esul o ase ieso expe imen als udies,acompu a ionallye icien 
a chi ec u ewaschosenbasedon he as Tex me hodandi s ools(Jouline al.
2016).Thisme hodp o ideswo dembeddingsandes ima es hep obabili y
dis ibu iono documen sacco ding op ede inedclasses.Wo dsa ep esen ed
in ec o  o mbasedonau oma icwo dspli ingin opa s(subwo ds),which
simula es heopennesso  hedic iona y.Thesubwo dp esen a ionisimpo an 
since heUk ainianlanguageishighlyin lec i e,andplen yo unseenwo dsas
wellaswo dswi hspellinge o smus beco e ed.Thee ec i enesso  heused
app oachisalsode e minedby he echnicalcondi ionso sys emope a ionand
a ailable ex ual esou ces o model aining.
Ap epa edco puso app oxima ely12,000 ex documen swasused o bina y
classi ica ion ode ec  oxiccon en .Thebes  esul ,basedon hegene alized
me ic(F1=79.4%),wasachie edwi h he ollowinghype pa ame e se ings:
awo d ec o dimensionali yo 56,anini iallea ning a eo 0.15,500 aining
epochs,lexicalcon ex  ep esen edbybig ams,subwo dleng hs anging om
2 o 5 cha ac e s, and a decision h eshold o  0.4. Addi ionally, he model
demons a edasensi i i yo 85%whileachie inganaccu acyo app oxima ely
70%.
 S aipsniai / A icles 241
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(Techniques, Means, Func ionali y)
5.2. Au ho shipiden i ica ion
Expe imen al esea ch o  models o  ex  au ho ship iden i ica ion was
ca iedou usingapa o  heco puso publiclya ailablesocio-poli ical ex s,
inwhichi ispossible oiden i y hepe sonwhois heau ho o  hedocumen .
A o alo 702 ex s om ou au ho swhopublished hela ges numbe o 
documen sbe ween60and1000cha ac e swe eselec ed.Thela ges numbe 
o publica ionsby heau ho is304(115 housandcha ac e s),and hesmalles 
is109(49 housandcha ac e s).Fo  es ing,25 ex s o eachselec edau ho 
we e andomlysampled.The es o  hedocumen smadeup he ainingse .
Thebes  esul ,acco ding o hegene alizedme ic(F1=81%),wasachie ed
wi h he ollowinghype pa ame e  alues:awo dembeddingspacedimension
o  50, an ini ial lea ning a e o  0.1, 50 aining epochs, lexical con ex 
ep esen edbybig ams,subwo dleng hs anging om2 o5cha ac e s,and
adecision-making h esholdo 0.5.No ably, o ce ainmodelcon igu a ions,
hesensi i i y o heau ho wi h hela ges numbe o documen sin heda ase 
eached100%,wi hanaccu acyexceeding90%.These esul sdemons a e he
easibili yo de elopingane ec i esys emcapableo accu a elyco e ing ex s
byau ho swhoa esu icien ly ep esen edin he ainingse .
The ainedneu alne wo kmodelswe ein eg a edin o heTex A ibu o 
sys emin he“clien -se e ”a chi ec u e,whe e he esul so  wo asksa e
p esen ed:(a) oxici yde e mina ionand(b)au ho shipde ec ion.The esul 
o  hesys em’swo kon he ex o  he“Lawo Uk aineonHighe Educa ion”:
Toxici yindex(es ima ein he o mo p obabili y: how oxic he ex is)–
0.04, simila i y wi h au ho s (es ima ions in he o m o  he p obabili y o 
au ho ship o au ho sknown o hesys em):0.49 o I.Fa ion,0.30 o Oleksii
Honcha enko,and0.22 o Ma ianaBezuhla.
6. CONCLUSIONS
TheTex A ibu o sys emiscu en lyunde going es ingphases oadd ess
a ibu ionand oxici yde e mina ionissueswi hinUk ainian-language ex s.
Thissys emisbo hcon enien ande ec i e o  a ious echnologicals udies.
O e 5mon hs, heTex A ibu o webapplica ionhasau oma icallyanalyzed
784Uk ainian ex sby226use s.
Ou  indingsdemons a e hee ec i enesso ou me hod,whichin ol es
quan izing e balelemen sbasedon o malg amma icalandseman icpa ame e s,
pa icula ly o nega i eemo ionali y.Thisisachie ed h oughacombina ion
o dic iona yand ule-basedapp oaches,complemen edbymachinelea ning
NATALIIA DARCHUK, OKSANA ZUBAN, VALENTYNA ROBEIKO,
YULIIA TSYHVINTSEVA, VICTOR SOROKIN, MYKOLA SAZHOK
242 Ac aLinguis icaLi huanicaXCI
echniques.Expe imen almachinelea ning esea ch o  oxici yde ec ionand
au ho ship iden i ica ion by ex  allowed us oob ain esul s compa able o
esul so expe imen swi hsimila modelcha ac e is ics(numbe o documen s
andau ho s) epo ed o o he languages.Subwo dmodelsshowedenhanced
obus nessagains lexicalopennessand ex uale o s.
Theconduc ed esea chpa es heway o sol ingsuchp oblems o Uk ainian
as de ec ingand moni o ing oxic con en ,ha e speechandmisin o ma ion,
au ho ship e i ica ion and deob usca ion, au ho  p o iling and dia izing,
psycholinguis ic p o iling, s yle modelling, and acking he sou ce o  ake
con en ,e c.Thede eloped ex analysisanda ibu ionschemecanalsobe
applied oo he languages.
Lookingahead,weplan oin eg a eou au oma ic ex a ibu ionand oxici y
de ec ion ool wi h seman ic, syn ac ic, psycholinguis ic, and sociolinguis ic
analysis.Thisin eg a ionwillgi eusadeepe unde s andingo  heimpac on
he eade .Byusingseman icanalysiso lexical axonomy,weaim oiden i y
na a i e elemen s inhe en  in he ex , he eby inc easing he eliabili y o 
ex a ibu ioninau ho shipiden i ica ionp ocedu es.Inaddi ion,weplan
oexpandou  ex co po aandu ilizemul ilingualla gelanguagemodels o
u he ex end hecapabili ieso ou sys emaswellas oimplemen  ools o 
s a is ical ex compa ison o alls yleso  heUk ainianlanguage.
Acknowledgemen s
The sys em has been c ea ed wi hin a p ojec  suppo ed by he B i ish
EmbassyinKyi andca iedou bya eamo educa o sand esea che so  he
Uk ainianLanguageandAppliedLinguis icsChai ,Ta asShe chenkoNa ional
Uni e si yo Kyi .
Wewouldlike oexp essou since eapp ecia ion o heB i ishEmbassy
inKyi  o  hei  inancialsuppo o  his esea chp ojec .Wea eg a e ul o
S i lanaYa o skaandI ynaBezko o ayna o  hei guidanceandassis ance
h oughou  he p ojec . Special hanks o Kos ian yn Goncha enko o  he
o ganiza ion and documen a y suppo  o  he p ojec . Fu he mo e, we a e
g a e ul o he s uden s o  he educa ional p og am “Applied (Compu e )
Linguis icsandEnglishLanguage”o Ta asShe chenkoNa ionalUni e si y
o Kyi .Theyha econ ibu ed hei  ime,expe ise,ande o s o o ming
heco puso Uk ainian oxic ex s.Wea eg a e ul oOksana Tolochko,a
g adua eo ou bachelo ’sdeg eep og am, o c ea inga onaldic iona yo  he
Uk ainianlanguage,whichweused ocompilealexicog aphiclis o nega i e
emo iogens.Addi ionally,wea edeeplyapp ecia i eo  hee o smadeby
MykolaKos iko in heda acollec ionp ocess.Wewouldlike oexp essou 
since eg a i ude oallmembe so  he esea chcommuni ywhocon ibu ed o
hiss udywi h hei ad iceandconsul a ions.
 S aipsniai / A icles 243
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o Uk ainian Media Tex s Tex A ibu o 1.0
(Techniques, Means, Func ionali y)
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246 Ac aLinguis icaLi huanicaXCI
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10.31558/1815-3070.2019.38.15.
Uk ainosžiniasklaidos eks ųau oma inės
s ilome inėsanalizėssis ema
„Tex A ibu o 1.0“
(me odai,p iemonės, unkcionalumas)
SANTRAUKA
Sis ema „Tex A ibu o “ s a is iškai pa ame izuoja uk ainiečių kalbos eks us au o-
ys ėsa pažinimoi nuo aikųanalizėsaspek ais.Naudodamadaugiapa ame inį15s a is i-
niųindeksų inkinį,„Tex A ibu o “apibūdinaau o iness ilis inesypa ybes.Jiin eg uoja
okiusme oduskaipkomponen inėanalizė,paski s ymoanalizė,k an a imasi nuo ai-
kųanalizėpanaudojan  žodynusi  mašininiomokymosime odus, ski usnemandagaus
eks oi au o ys ėsišaiškinimui.Sis emaapdo oja eks us aikydama okeniza imą,mo -
ologinįžymėjimą,kon eks inęi sin aksinęanalizęi emociškaineigiamožodynoa i iki-
mą,leidžian įišsamiai izualizuo ii ekspe iškaiį e in i eks op isky imąi neigiamą
u inį.Ekspe imen aipa i inasis emosgebėjimąnus a y iunikaliusau o iausb uožus
i į e in i eks opanašumą,ypačpoli iniodisku soi nemandagioskomunikacijosžinias-
klaidoskon eks eRusijosi Uk ainoska ome u.S aipsnyjepab ėžiamap ak inėi  eo i-
nė„Tex A ibu o “ eikšmė,demons uojan jose ek y umądidelėms eks oapim imsi 
iksliomsanali inėmsgalimybėms.Sėkmingasžodynais, aisyklėmispag įs ųi mašininio
mokymosime odų aikymaspab ėžiasis emos i umąi uni e salumą.Be a e sijai  e-
be ykdomų y imų ezul a aiy anuodugniaiišnag inė i,obūsimosjųk yp ysnus a omos
siekian išplės ikalbinįko pusąi  obulin imašininiomokymosimodelius,siekian page-
in i ikslumąi p i aikomumą.
 S aipsniai / A icles 247
The Sys em o Au oma ic S ylome ic Analysis
o Uk ainian Media Tex s Tex A ibu o 1.0
(Techniques, Means, Func ionali y)
Į eik a2024m.lapk ičio25d.
NATALIIADARCHUK
Ta as She chenko Na ional Uni e si y o Kyi
60 Volodymy ska S ee
Kyi , 01033, Uk aine
n.da [email protected]
OKSANAZUBAN
Ta as She chenko Na ional Uni e si y o Kyi
60 Volodymy ska S ee
Kyi , 01033, Uk aine
[email protected]
VALENTYNAROBEIKO
Ta as She chenko Na ional Uni e si y o Kyi
60 Volodymy ska S ee
Kyi , 01033, Uk aine
alen yna. obeik[email p o ec ed]
YULIIATSYHVINTSEVA
Ta as She chenko Na ional Uni e si y o Kyi
60 Volodymy ska S ee
Kyi , 01033, Uk aine
Ins i u e o he Uk ainian Language o
he Na ional Academy o Sciences o Uk aine
4 Mykhailo H ushe skyi S ee
Kyi , 01001, Uk aine
juli o[email p o ec ed]
VICTORSOROKIN
Ta as She chenko Na ional Uni e si y o Kyi
60 Volodymy ska S ee
Kyi , 01033, Uk aine
ic o .so ok[email p o ec ed]
MYKOLASAZHOK
Ins i u e o in o ma ion echnologies and sys ems
o he Na ional Academy o Sciences o Uk aine
40 Akademika Hlushko a A enue
Kyi , 03187, Uk aine
s[email p o ec ed]om