Identifying Reproductive Behavior Arguments in Social Media Content Users' Opinions through Natural Language Processing Techniques
Irina Kalabikhina (),
Ekaterina Zubova (),
Natalia Loukachevitch (),
Anthony Kolotusha (),
Zarina Kazbekova (),
Evgeny Banin () and
German Klimenko ()
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Irina Kalabikhina: Lomonosov Moscow State University, Moscow, Russia
Ekaterina Zubova: Yale University, New Haven, United States of America
Natalia Loukachevitch: Lomonosov Moscow State University, Moscow, Russia
Anthony Kolotusha: Lomonosov Moscow State University, Moscow, Russia
Zarina Kazbekova: Lomonosov Moscow State University, Moscow, Russia
Evgeny Banin: Kurchatov Institute, Moscow, Russia
German Klimenko: Lomonosov Moscow State University, Moscow, Russia
Population and Economics, 2023, vol. 7, issue 2, 40-59
Abstract:
Big data provides researchers with valuable sources of information for studying demographic behavior in the population. One such source is the texts posted by social network users on various demographic issues. This study utilizes methods for automatically extracting user opinions from the "VKontakte" social network. The extracted texts are then classified using the Conversational RuBERT neural network model to investigate opinions related to reproductive behavior in the population. The classification process addresses two consecutive problems. Firstly, it aims to identify whether a user's comment contains argumentation. Secondly, if an argument is present, it seeks to determine its type within the context of the "personal-public" dichotomy. To search for arguments and classify their types, six experiments were conducted, varying the dataset and the number of classes. The method employed for automatic extraction and classification of user opinions on the "VKontakte" social network has demonstrated the ability to accurately classify users' comments, identifying the presence of argumentation and categorizing the arguments within the "personal-public" dichotomy. This enables the identification of personal and social attitudes, values, stories, and opinions, thus facilitating the study of reproductive behavior.
Keywords: reproductive; behavior; personal-public; dichotomy; automatic; opinion; extraction; argumentation; VKontakte; Conversational; RuBERT (search for similar items in EconPapers)
JEL-codes: C8 J1 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:arh:jpopec:v:7:y:2023:i:2:p:40-59
DOI: 10.3897/popecon.7.e97064
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