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Program Systems: Theory and Applications, 2021, Volume 12, Issue 4, Pages 33–63
DOI: https://doi.org/10.25209/2079-3316-2021-12-4-33-63
(Mi ps388)
 

This article is cited in 2 scientific papers (total in 2 papers)

Artificial Intelligence, Intelligent Systems, Neural Networks

Automatic extraction of social network users' attitudes on reproductive behavior issues

I. E. Kalabikhinaa, N. V. Lukashevicha, E. P. Baninb, K. V. Alibaevaa, S. M. Rebreyc

a Lomonosov Moscow State University
b National Research Center “Kurchatov Institute”
c Moscow State Institute of International Relations (MGIMO)
References:
Abstract: This paper presents a specialized dataset with annotation of user attitudes on reproductive behavior. We analyze the features of the “for” and “against” stance distribution for specific aspects of reproductive behavior. The created dataset solves two classification problems: classifying messages by the relevance to a topic being studied and the author’s stance on a particular issue. We use classical machine learning methods and the BERT-based neural network classified messages models. The best classification results in both tasks are achieved based on variants of the BERT model using pairs of sentences in the classification — variants of NLI (natural language inference) and QA (question-answering). In addition, the created dataset makes it possible to draw meaningful conclusions on the attitudes of VKontakte users to reproductive behavior issues. It was revealed that the phenomenon of deliberate childlessness is actively represented in VKontakte groups while having many children remains a poorly widespread model of behavior. Within the framework of the pro-natalist policy, it is crucial to form a favorable public opinion about parenting, to alleviate the deficiency of time for parents.
Key words and phrases: opinion analysis, BERT, supervised learning, demographic policy, VKontakte, reproductive behavior.
Funding agency Grant number
Ministry of Education and Science of the Russian Federation ÀÀÀÀ-À17-117062610054-1
Russian Science Foundation 21-71-30003
The work was a part of the research work “Reproduction of the population in the context of socio-economic development” AAAA-A17-117062610054-1).
This research has been supported by the Interdisciplinary Scientific and Educational School of Moscow University «Brain, Cognitive Systems, Artificial Intelligence».
The work was supported by the Russian Science Foundation grant 21-71-30003 in terms of creating the annotation interface, annotation itself, and methodology for applying machine learning methods.
Received: 10.11.2021
Accepted: 30.12.2021
Document Type: Article
UDC: 519.689.3:007.51
BBC: 32.973.202-018.2
MSC: Primary 97P30; Secondary 97P20, 97R40
Language: Russian
Citation: I. E. Kalabikhina, N. V. Lukashevich, E. P. Banin, K. V. Alibaeva, S. M. Rebrey, “Automatic extraction of social network users' attitudes on reproductive behavior issues”, Program Systems: Theory and Applications, 12:4 (2021), 33–63
Citation in format AMSBIB
\Bibitem{KalLukBan21}
\by I.~E.~Kalabikhina, N.~V.~Lukashevich, E.~P.~Banin, K.~V.~Alibaeva, S.~M.~Rebrey
\paper Automatic extraction of social network users' attitudes on reproductive behavior issues
\jour Program Systems: Theory and Applications
\yr 2021
\vol 12
\issue 4
\pages 33--63
\mathnet{http://mi.mathnet.ru/ps388}
\crossref{https://doi.org/10.25209/2079-3316-2021-12-4-33-63}
Linking options:
  • https://www.mathnet.ru/eng/ps388
  • https://www.mathnet.ru/eng/ps/v12/i4/p33
  • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Program Systems: Theory and Applications
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