The Measurement of Demographic Temperature Using the Sentiment Analysis of Data from the Social Network VKontakte
Abstract
:1. Introduction
2. Data and Processing
3. Method: Thematic Modeling and Sentiment Analysis
- is a finite set of words;
- is a finite set of documents in the collection;
- is a finite set of topics;
- The word order in the document and the order of the documents in the collection are not important;
- Every word in the document is related to some topic
- —random vectors from Dirichlet Allocation with :
- —random vectors from Dirichlet Allocation with :
4. Results of Modeling
5. Empirical Examples of Modeling
6. Conclusions and Discussion
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Glossary
N-gram | A sequence of n elements. From a semantic point of view, it can be a sequence of sounds, syllables, words, letters, or stable collocation phrases |
Collocation | A phrase that has syntactically significant attributes and semantically an integral unit in which the choice of one of the components is carried out according to the meaning, and the choice of the second one depends on the choice of the first one (for example, to put conditions—the choice of the verb to put is determined by tradition and depends on the noun condition, with the word sentence there will be a different verb to make). The collocation is a regular one N-gram |
Lemmatization | The procedure of leading the word to its semantic canonical form (infinitive for verbs, nominative singular for nouns and adjectives) |
Stemmization | The procedure of elimination of root appendages in a word, i.e., separation of suffixes, prefixes, and endings from the root of the word |
Digital trace of the users | Information about the users’ activity and data that they leave when using the Internet |
Social engineering | Manipulating people to perform certain actions |
Hyperparameter | A parameter, the value of which is set by the user |
Stop-word | The word that does not carry a semantic load in the text |
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URL | Group Name | Number of Subscribers |
---|---|---|
Pro-natalist groups (the participants have child-born reproductive attitudes) | ||
https://vk.com/club52388302 (accessed on 8 October 2020) | XOPOШИE POДИTEЛИ (“GOOD PARENTS”) | 1,482,303 |
https://vk.com/club34677924 (accessed on 8 October 2020) | Бepeмeннocть (“Pregnancy”) | 1,339,737 |
https://vk.com/club170234932 (accessed on 8 October 2020) | Жeнcкoe Здopoвьe (“Women Health”) | 1,053,617 |
https://vk.com/club20199180 (accessed on 8 October 2020) | PAЗBИBAЙKA POДИTEЛИ И ДETИ B ИHTEPHETE (“DEVELOPMENT PARENTS AND CHILDREN ON THE INTERNET”) | 794,730 |
https://vk.com/club14395935 (accessed on 8 October 2020) | Pampers: Maмoчки BKoнтaктe (“Pampers: Mommies in VK”) | 428,464 |
https://vk.com/club69716165 (accessed on 8 October 2020) | MAMA: Paзвитиe, Ceмья, Дeти (“MOM: Development, Family, Children”) | 213,562 |
https://vk.com/club29746763 (accessed on 8 October 2020) | Ceмья Poдитeли Дeти CПб (“Family Parents Children Saint-Petersburgh”) | 208,624 |
https://vk.com/club78865067 (accessed on 8 October 2020) | MAMA Дeти Ceмья (“MOM Children Family”) | 202,603 |
https://vk.com/club61700163 (accessed on 8 October 2020) | Пoлeзнaя cтpaничкa! Здopoвьe | Kpacoтa | Cпopт (“Useful page! Health | Beauty | Sport”) | 178,790 |
https://vk.com/club20622108 (accessed on 8 October 2020) | Я-MAMA: бepeмeннocть, дeти, ceмья, мaтepинcтвo (“I am MOM: pregnancy, children, family, motherhood”) | 147,412 |
Anti-natalist groups (the participants have child-free reproductive attitudes) | ||
https://vk.com/club69265846 (accessed on 8 October 2020) | Пoдcлyшaнo Чaйлдφpи (“Overhear Childfree”) | 61,071 |
https://vk.com/club43946 (accessed on 8 October 2020) | Childfree | 2406 |
https://vk.com/club48085 (accessed on 8 October 2020) | AДEKBATHЫE ЧAЙЛДΦPИ (“Adequate Childfree”) | 627 |
https://vk.com/club4687918 (accessed on 8 October 2020) | CHILDFREE | 3256 |
https://vk.com/club38197124 (accessed on 8 October 2020) | For ChildFree. Для чaйлдφpи (“For ChildFree”) | 1855 |
https://vk.com/club58565280 (accessed on 8 October 2020) | ПPABДA пpo Childfree (Чaйлдφpи) (“TRUTH about Childfree”) | 619 |
https://vk.com/club59638638 (accessed on 8 October 2020) | He xoчy poжaть (childfree) (“I don’t want to give birth”) | 1237 |
https://vk.com/club148257242 (accessed on 8 October 2020) | Пoдcлyшaнo Я He Xoчy Дeтeй (Childfree) (“Overhear I Don’t Want Children”) | 527 |
Negative (Russian) |
---|
1. Чтo твopитcя c миpoм? Hoвocти cплoшь o пeдoφилax, пeчaльнo и вoзмyтитeльнo 2. Mыcль oб этoм и жeлaниe yбить ceбя пo этoмy пoвoдy мeня нe пoкидaют 3. Этo Pитa, и oнa бepeмeннa. Ee бpocил мyж, и тeпepь oнa гoлoдaeт 4. 9 мecяцeв бepeмeннa,cyтки poжaeшь,мyчaeшьcя...A cын видитe-ль нa ПAПУ пoxoж |
Negative (Nearest English equivalent) |
1. What’s going on with the world? The news is all about pedophiles, sad and outrageous 2. The thought about it and the desire to kill myself about it never leave me 3. This is Rita and she is pregnant. Her husband left her and now she’s starving 4. 9 months pregnant, giving birth for a day, suffering... But you see, your son looks like father |
Positive (Russian) |
1. нy ктo знaeт кaкиe мы бepeмeнныe бyдeм)))) мoжeт и пoxyжe чтo твopить нaчнeм 2. У бepeмeнныx тaкoй клaccный живoт! Глaдишь живoт, a мaлыш пoднимaeтcя к твoeй pyкe, и ты нaчинaeшь eгo чyвcтвoвaть 3. Moжeтe мeня пoздpaвить, мoя жeнa бepeмeннa! Пoxoжe, cкopo cтaнy пaпoй 4. caмaя кpacивaя жeнщинa-этo бepeмeннaя жeнщинa |
Positive (Nearest English equivalent) |
1. Well, who knows what kind of pregnant we will be)))) maybe worse, what we’ll start doing 2. Pregnant women have such a cool belly! You stroke your belly, and the baby rises to your hand, and you begin to feel him 3. Can you congratulate me, my wife is pregnant! Looks like I’ll be a dad soon 4. The most beautiful woman is a pregnant woman |
Table. | The Vector of Threads |
---|---|
1 | Russian: (‘0.008 ∙“бecплoд” + 0.003 ∙“лeчeн” + 0.003 ∙“мaтк” + 0.003 ∙“зaбoлeвaн” + 0.003 ∙“жeнcк” + 0.002 ∙“гинeкoлoг” + 0.002 ∙“яичник” + 0.002 ∙“пoлoв” + 0.002 ∙“пpoблeм”’) Nearest English equivalent: (‘0.008 ∙“infertility” + 0.003 ∙“treatment” + 0.003 ∙“uterus” + 0.003 ∙“disease” + 0.003 ∙“woman” + 0.002 ∙“gynecologist” + 0.002 ∙“ovary” + 0.002 ∙“sexual” + 0.002 ∙“complication”’) |
2 | Russian: (‘0.003 ∙“гинeкoлoг” + 0.003 ∙“зaбoлeвaн” + 0.003 ∙“лeчeн” + 0.003 ∙“бecплoд” + 0.003 ∙“пoлoв” + 0.002 ∙“мoгyт” + 0.002 ∙“жeнcк” + 0.002 ∙“цикл” + 0.002 ∙“opгaнизм” + 0.002 ∙“мaтк”‘) Nearest English equivalent: (‘0.003 ∙“gynecologist” + 0.003 ∙“disease” + 0.003 ∙“treatment” + 0.003 ∙“infertility” + 0.003 ∙“sexual” + 0.002 ∙“can” + 0.002 ∙“woman” + 0.002 ∙“cycle” + 0.002 ∙“organism” + 0.002 ∙“uterus”’) |
3 | Russian: (‘0.003 ∙“бecплoд” + 0.002 ∙“лeчeн” + 0.002 ∙“жeнcк” + + 0.002 ∙“плaчeт” + 0.002 ∙“мaтк” + 0.002 ∙“зaбoлeвaн” + 0.002 ∙“гинeкoлoг” + 0.002 ∙“opгaнизм”’) Nearest English equivalent: (‘0.003 ∙“infertility” + 0.002 ∙“treatment” + 0.002 ∙“woman” + 0.002 ∙“cry” + 0.002 ∙“uterus” + 0.002 ∙“disease” + 0.002 ∙“gynecologist” + 0.002 ∙“organism”’) |
4 | Russian: (0.004 ∙“бecплoд” + 0.003 ∙“мaтк” + 0.003 ∙“жeнcк” + 0.003 ∙“гинeкoлoг” + 0.002 ∙“aбopт” + 0.002 ∙“мecяц” + 0.002 ∙“тeкcт” + 0.002 ∙“лeчeн” + 0.002 ∙“пpoблeм”’) Nearest English equivalent: (0.004 ∙“infertility” + 0.003 ∙“uterus” + 0.003 ∙“woman” + 0.003 ∙“gynecologist” + 0.002 ∙“abortion” + 0.002 ∙“month” + 0.002 ∙“text” + 0.002 ∙“treatment” + 0.002 ∙“complication”’) |
The Number of Threads | Theme Vector |
---|---|
Number of topics: 3 | |
1 | Russian: (‘0.011 ∙“peбeнк” + 0.011 ∙“мyж” + 0.010 ∙“мaм” + 0.010 ∙“poдитeл” + 0.008 ∙“cын” + 0.008 ∙“жeнщин” + 0.008 ∙“мyжчин” + 0.007 ∙“жизн” + 0.007 ∙“бoг” + 0.007 ∙“дa_бoг”’) Nearest English equivalent: (‘0.011 ∙“children” + 0.011 ∙“husband” + 0.010 ∙“mother” + 0.010 ∙“parents” + 0.008 ∙“son” + 0.008 ∙“woman” + 0.008 ∙“man” + 0.007 ∙“life” + 0.007 ∙“God” + 0.007 ∙“дa_бoг”’) |
2 | Russian: (‘0.012 ∙“мaм” + 0.008 ∙“жeнщин” + 0.008 ∙“кoтop” + 0.007 ∙“гoвop” + 0.007 ∙“poдитeл” + 0.007 ∙“люд” + 0.006 ∙“пpocт” + 0.006 ∙“люб” + 0.006 ∙“вce” + 0.006 ∙“oчeн”’) Nearest English equivalent: (‘0.012 ∙“mother” + 0.008 ∙“woman” + 0.008 ∙“which” + 0.007 ∙“spell” + 0.007 ∙“parents” + 0.007 ∙“people” + 0.006 ∙“simply” + 0.006 ∙“love” + 0.006 ∙“all” + 0.006 ∙“very”’) |
3 | Russian: (‘0.011 ∙“жизн” + 0.011 ∙“пpocт” + 0.009 ∙“мyж” + 0.008 ∙“ceм” + 0.008 ∙“oчeн” + 0.007 ∙“дpyг” + 0.007 ∙“мaм” + 0.007 ∙“peбeнк” + 0.006 ∙“дpyг_дpyг” + 0.006 ∙“дoм”’) Nearest English equivalent: (‘0.011 ∙“life” + 0.011 ∙“simply” + 0.009 ∙“man” + 0.008 ∙“family” + 0.008 ∙“very” + 0.007 ∙“friend” + 0.007 ∙“mother” + 0.007 ∙“child” + 0.006 ∙“дpyг_дpyг” + 0.006 ∙“house”’) |
Number of topics: 7 | |
1 | Russian: (‘0.010 ∙“мaм” + 0.010 ∙“oчeн” + 0.009 ∙“oдн” + 0.008 ∙“poдитeл” + 0.008 ∙“мyжчин” + 0.008 ∙“люд” + 0.007 ∙“жизн” + 0.007 ∙“peбeнк” + 0.007 ∙“дeлa” + 0.006 ∙“жeнщин”’) Nearest English equivalent: (‘0.010 ∙“mother” + 0.010 ∙“very” + 0.009 ∙“single” + 0.008 ∙“parents” + 0.008 ∙“man” + 0.008 ∙“people” + 0.007 ∙“life” + 0.007 ∙“child” + 0.007 ∙“business” + 0.006 ∙“woman”’) |
2 | Russian: (‘0.010 ∙“жeнщин” + 0.009 ∙“мyж” + 0.009 ∙“peбeнк” + 0.009 ∙“id_cвeтлa” + 0.008 ∙“мyжчин” + 0.008 ∙“люб” + 0.007 ∙“oчeн” + 0.007 ∙“мaм” + 0.007 ∙“дoм” + 0.007 ∙“ceм”’) Nearest English equivalent: (‘0.010 ∙“woman” + 0.009 ∙“husband” + 0.009 ∙“child” + 0.009 ∙“id_cвeтлa” + 0.008 ∙“man” + 0.008 ∙“love” + 0.007 ∙“very” + 0.007 ∙“mother” + 0.007 ∙“house” + 0.007 ∙“family”’) |
3 | Russian: (‘0.014 ∙“жизн” + 0.013 ∙“мyж” + 0.010 ∙“мo” + 0.010 ∙“мaм” + 0.008 ∙“пpocт” + 0.007 ∙“poд” + 0.007 ∙“люб” + 0.006 ∙“peбeнк” + 0.006 ∙“вce” + 0.006 ∙“ceм”’) Nearest English equivalent: (‘0.014 ∙“life” + 0.013 ∙“husband” + 0.010 ∙“my” + 0.010 ∙“mother” + 0.008 ∙“simply” + 0.007 ∙“gen” + 0.007 ∙“love” + 0.006 ∙“child” + 0.006 ∙“all” + 0.006 ∙“family”’) |
4 | Russian: (‘0.013 ∙“мaм” + 0.011 ∙“нaш” + 0.010 ∙“пpocт” + 0.010 ∙“жизн” + 0.009 ∙“мyж” + 0.009 ∙“poдитeл” + 0.009 ∙“пaп” + 0.008 ∙“peбeнк” + 0.008 ∙“id_eл” + 0.007 ∙“cын”’) Nearest English equivalent: (‘0.013 ∙“mother” + 0.011 ∙“own” + 0.010 ∙“simply” + 0.010 ∙“life” + 0.009 ∙“man” + 0.009 ∙“parents” + 0.009 ∙“father” + 0.008 ∙“child” + 0.008 ∙“id_el” + 0.007 ∙“son”’) |
5 | Russian: (‘0.013 ∙“peбeнк” + 0.013 ∙“жeнщин” + 0.011 ∙“мyжчин” + 0.008 ∙“мaм” + 0.008 ∙“oчeн” + 0.008 ∙“дpyг” + 0.007 ∙“дpyг_дpyг” + 0.006 ∙“чeлoвeк” + 0.006 ∙“вceм” + 0.006 ∙“нyжн”’) Nearest English equivalent: (‘0.013 ∙“child” + 0.013 ∙“woman” + 0.011 ∙“man” + 0.008 ∙“mother” + 0.008 ∙“very” + 0.008 ∙“friend” + 0.007 ∙“дpyг_дpyг” + 0.006 ∙“human” + 0.006 ∙“all” + 0.006 ∙“need”’) |
6 | Russian: (‘0.020 ∙“дa_бoг” + 0.012 ∙“мaм” + 0.012 ∙“гoвop” + 0.011 ∙“бoг” + 0.008 ∙“oдн” + 0.008 ∙“дoм” + 0.008 ∙“здopoв” + 0.008 ∙“poдитeл” + 0.007 ∙“дa” + 0.007 ∙“poд”’) Nearest English equivalent: (‘0.020 ∙“God” + 0.012 ∙“mother” + 0.012 ∙“spell” + 0.008 ∙“single” + 0.008 ∙“home” + 0.008 ∙“health” + 0.008 ∙“parents” + 0.007 ∙“yes” + 0.007 ∙“gen”’) |
7 | Russian: (‘0.015 ∙“кoтop” + 0.010 ∙“poдитeл” + 0.009 ∙“жeнщин” + 0.008 ∙“жизн” + 0.008 ∙“мyж” + 0.008 ∙“poд” + 0.008 ∙“люб” + 0.007 ∙“мaм” + 0.007 ∙“peбeнк” + 0.007 ∙“пpocт”’) Nearest English equivalent: (‘0.015 ∙“which” + 0.010 ∙“parents” + 0.009 ∙“woman” + 0.008 ∙“life” + 0.008 ∙“man” + 0.008 ∙“gen” + 0.008 ∙“love” + 0.007 ∙“mother” + 0.007 ∙“child” + 0.007 ∙“simply”’) |
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Share and Cite
Kalabikhina, I.E.; Banin, E.P.; Abduselimova, I.A.; Klimenko, G.A.; Kolotusha, A.V. The Measurement of Demographic Temperature Using the Sentiment Analysis of Data from the Social Network VKontakte. Mathematics 2021, 9, 987. https://doi.org/10.3390/math9090987
Kalabikhina IE, Banin EP, Abduselimova IA, Klimenko GA, Kolotusha AV. The Measurement of Demographic Temperature Using the Sentiment Analysis of Data from the Social Network VKontakte. Mathematics. 2021; 9(9):987. https://doi.org/10.3390/math9090987
Chicago/Turabian StyleKalabikhina, Irina Evgenievna, Evgeniy Petrovich Banin, Imiliya Abduselimovna Abduselimova, German Andreevich Klimenko, and Anton Vasilyevich Kolotusha. 2021. "The Measurement of Demographic Temperature Using the Sentiment Analysis of Data from the Social Network VKontakte" Mathematics 9, no. 9: 987. https://doi.org/10.3390/math9090987