Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Analyzing Longitudinal Development of Thematic Clusters Content in Scientific Texts. / Pimenov, Ivan; Salomatina, Natalia.
SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. стр. 844-849 8958227 (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Analyzing Longitudinal Development of Thematic Clusters Content in Scientific Texts
AU - Pimenov, Ivan
AU - Salomatina, Natalia
N1 - Funding Information: ACKNOWLEDGMENT The work was supported by the program of Fundamental Scientific Researches of the RAS, project N 0314-2019-15 and by RFBR, the research project N 18-00-01376 (18-00-00760). Publisher Copyright: © 2019 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/10
Y1 - 2019/10
N2 - In this paper we present the results of a study devoted to identification of longitudinal changes that occur in a given research field. The approach that is employed is based on full text analysis. Extraction of terms and their relations, along with thematic clustering are performed by the use of the freely distributed VOSViewer software. The latter allows to detect terms in the form of noun phrases and to cluster these terms with the help of a modularity based algorithm. Longitudinal development of the constructed thematic clusters is analyzed through the use of directed graphs that are built to reflect significant changes in their content at the level of their formation and development over successive subperiods. An alluvial diagram is employed to show the overall transformation of the thematic clusters. The utilized approach is applied to the proceedings of 'EuropaCat' catalysis conferences over a ten-year period. The conducted analysis shows that thematic clusters identified for the processed data are characterized by a low degree of stability. Even then, shifts of the researchers' interests from one theme to another can be clearly observed. Three most frequent types of cluster transformation are recognized: 1) continuance of a theme; 2) emergence of a new theme with its steady further growth; 3) emergence and discontinuance of a new theme. Main tendencies of temporal development of the detected thematic clusters are characterized in quantitative aspects.
AB - In this paper we present the results of a study devoted to identification of longitudinal changes that occur in a given research field. The approach that is employed is based on full text analysis. Extraction of terms and their relations, along with thematic clustering are performed by the use of the freely distributed VOSViewer software. The latter allows to detect terms in the form of noun phrases and to cluster these terms with the help of a modularity based algorithm. Longitudinal development of the constructed thematic clusters is analyzed through the use of directed graphs that are built to reflect significant changes in their content at the level of their formation and development over successive subperiods. An alluvial diagram is employed to show the overall transformation of the thematic clusters. The utilized approach is applied to the proceedings of 'EuropaCat' catalysis conferences over a ten-year period. The conducted analysis shows that thematic clusters identified for the processed data are characterized by a low degree of stability. Even then, shifts of the researchers' interests from one theme to another can be clearly observed. Three most frequent types of cluster transformation are recognized: 1) continuance of a theme; 2) emergence of a new theme with its steady further growth; 3) emergence and discontinuance of a new theme. Main tendencies of temporal development of the detected thematic clusters are characterized in quantitative aspects.
KW - co-word analysis
KW - directed graph
KW - evolution of research fields
KW - longitudinal development
KW - thematic cluster
UR - http://www.scopus.com/inward/record.url?scp=85079070892&partnerID=8YFLogxK
UR - https://elibrary.ru/item.asp?id=43251730
U2 - 10.1109/SIBIRCON48586.2019.8958227
DO - 10.1109/SIBIRCON48586.2019.8958227
M3 - Conference contribution
AN - SCOPUS:85079070892
T3 - SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
SP - 844
EP - 849
BT - SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019
Y2 - 21 October 2019 through 27 October 2019
ER -
ID: 27889602