Sociology of values: experience of building a taxonomy by using natural language analysis technology

Modern research in the field of sociology of science is becoming more complicated due to the constantly growing publication activity of authors. To track trends in sectoral sociology, scientists turn to scientometric methods, but they are not enough. Trends in the development of the sociology of val...

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Main Authors: M. A. Kashina, S. Tkach
Format: Article
Language:Russian
Published: State University of Management 2023-04-01
Series:Цифровая социология
Subjects:
Online Access:https://digitalsociology.guu.ru/jour/article/view/235
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author M. A. Kashina
S. Tkach
author_facet M. A. Kashina
S. Tkach
author_sort M. A. Kashina
collection DOAJ
description Modern research in the field of sociology of science is becoming more complicated due to the constantly growing publication activity of authors. To track trends in sectoral sociology, scientists turn to scientometric methods, but they are not enough. Trends in the development of the sociology of values as a branch of sociology are the subject of the study. The purpose of the work is an assessment of the possibilities of using natural language analysis methods (NLP/NLA) for thematic and theoretical clustering of research in the sociology of values. The design of the study was quantitative and qualitative, it was carried out in two stages. At the first stage, 121 abstracts of a scientific articles were analyzed using text mining, after which their total array was divided into clusters. At the second stage, the results of machine clustering were examined by the method of qualitative text analysis, on the basis of which the limitations and capabilities of the NLP/NLA method were identified for solving the problem of clustering scientific texts. It was found that articles with a more conservative core of theoretical categories (gender studies, migration studies, the theory of globalism) are more amenable to clustering, while theories with a loosely structured and fluid theoretical core (theories using environmental terminology, theories of inequality) are much less amenable to explicit clustering. The results obtained allow us to form a new direction of work with large arrays of scientific texts, associated with their clustering using NLP/NLA. Building clusters enables researchers to work with all texts in a given subject area, and not just with the most cited ones. This, in turn, provides the visibility of all scientific ideas, including those that have not gained popularity/notability.
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spelling doaj.art-a7cac2e5ad7246fcba59ec79c699a2ca2024-04-23T13:09:47ZrusState University of ManagementЦифровая социология2658-347X2713-16532023-04-0161485810.26425/2658-347X-2023-6-1-48-58147Sociology of values: experience of building a taxonomy by using natural language analysis technologyM. A. Kashina0S. Tkach1North-West Institute of Management – Branch of the Russian Presidential Academy of National Economy and Public AdministrationSt. Petersburg University Research ParkModern research in the field of sociology of science is becoming more complicated due to the constantly growing publication activity of authors. To track trends in sectoral sociology, scientists turn to scientometric methods, but they are not enough. Trends in the development of the sociology of values as a branch of sociology are the subject of the study. The purpose of the work is an assessment of the possibilities of using natural language analysis methods (NLP/NLA) for thematic and theoretical clustering of research in the sociology of values. The design of the study was quantitative and qualitative, it was carried out in two stages. At the first stage, 121 abstracts of a scientific articles were analyzed using text mining, after which their total array was divided into clusters. At the second stage, the results of machine clustering were examined by the method of qualitative text analysis, on the basis of which the limitations and capabilities of the NLP/NLA method were identified for solving the problem of clustering scientific texts. It was found that articles with a more conservative core of theoretical categories (gender studies, migration studies, the theory of globalism) are more amenable to clustering, while theories with a loosely structured and fluid theoretical core (theories using environmental terminology, theories of inequality) are much less amenable to explicit clustering. The results obtained allow us to form a new direction of work with large arrays of scientific texts, associated with their clustering using NLP/NLA. Building clusters enables researchers to work with all texts in a given subject area, and not just with the most cited ones. This, in turn, provides the visibility of all scientific ideas, including those that have not gained popularity/notability.https://digitalsociology.guu.ru/jour/article/view/235mixed methodsscientific textclusteringsocio-humanitarian knowledgenatural language processingnatural language assessmentward methodartificial intelligencestructuralismmetaphoractor theory
spellingShingle M. A. Kashina
S. Tkach
Sociology of values: experience of building a taxonomy by using natural language analysis technology
Цифровая социология
mixed methods
scientific text
clustering
socio-humanitarian knowledge
natural language processing
natural language assessment
ward method
artificial intelligence
structuralism
metaphor
actor theory
title Sociology of values: experience of building a taxonomy by using natural language analysis technology
title_full Sociology of values: experience of building a taxonomy by using natural language analysis technology
title_fullStr Sociology of values: experience of building a taxonomy by using natural language analysis technology
title_full_unstemmed Sociology of values: experience of building a taxonomy by using natural language analysis technology
title_short Sociology of values: experience of building a taxonomy by using natural language analysis technology
title_sort sociology of values experience of building a taxonomy by using natural language analysis technology
topic mixed methods
scientific text
clustering
socio-humanitarian knowledge
natural language processing
natural language assessment
ward method
artificial intelligence
structuralism
metaphor
actor theory
url https://digitalsociology.guu.ru/jour/article/view/235
work_keys_str_mv AT makashina sociologyofvaluesexperienceofbuildingataxonomybyusingnaturallanguageanalysistechnology
AT stkach sociologyofvaluesexperienceofbuildingataxonomybyusingnaturallanguageanalysistechnology