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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. p. 844-849 8958227 (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Pimenov, I & Salomatina, N 2019, Analyzing Longitudinal Development of Thematic Clusters Content in Scientific Texts. in SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings., 8958227, SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 844-849, 2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019, Novosibirsk, Russian Federation, 21.10.2019. https://doi.org/10.1109/SIBIRCON48586.2019.8958227

APA

Pimenov, I., & Salomatina, N. (2019). Analyzing Longitudinal Development of Thematic Clusters Content in Scientific Texts. In SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings (pp. 844-849). [8958227] (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIBIRCON48586.2019.8958227

Vancouver

Pimenov I, Salomatina N. Analyzing Longitudinal Development of Thematic Clusters Content in Scientific Texts. In SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 844-849. 8958227. (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings). doi: 10.1109/SIBIRCON48586.2019.8958227

Author

Pimenov, Ivan ; Salomatina, Natalia. / Analyzing Longitudinal Development of Thematic Clusters Content in Scientific Texts. SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 844-849 (SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings).

BibTeX

@inproceedings{e921805167ab4292bbd66036f428ee20,
title = "Analyzing Longitudinal Development of Thematic Clusters Content in Scientific Texts",
abstract = "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.",
keywords = "co-word analysis, directed graph, evolution of research fields, longitudinal development, thematic cluster",
author = "Ivan Pimenov and Natalia Salomatina",
note = "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: {\textcopyright} 2019 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2019 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2019 ; Conference date: 21-10-2019 Through 27-10-2019",
year = "2019",
month = oct,
doi = "10.1109/SIBIRCON48586.2019.8958227",
language = "English",
series = "SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "844--849",
booktitle = "SIBIRCON 2019 - International Multi-Conference on Engineering, Computer and Information Sciences, Proceedings",
address = "United States",

}

RIS

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