Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data

Kai, Naoto; Yoshihisa, Tomoki; Shimbaru, Toshiki; Yano, Hideto; Tanushi, Hideyuki

doi:https://doi.org/10.1007/978-3-031-46970-1_1

Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data

Kai, Naoto; Yoshihisa, Tomoki; Shimbaru, Toshiki et al.

Advances on P2P, Parallel, Grid, Cloud and Internet Computing (Lecture Notes on Data Engineering and Communications Technologies), 2023, 189, 1-13

アクセス数:718件（2025-11-06 13:37 集計）

固定URL: https://hdl.handle.net/11094/93143

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タイトル	Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data
著者	NRID 1000090940148 1000090940148 ORCID 0000-0003-3540-3689 0000-0003-3540-3689 researchmap permalink jr055 jr055 Scopus Author ID 57200498627 57200498627 著者名 Kai, Naoto
	NRID 1000000402743 1000000402743 著者名 Yoshihisa, Tomoki
	NRID 1000080964824 1000080964824 著者名 Shimbaru, Toshiki
	著者名 Yano, Hideto
	NRID 1000090973347 1000090973347 ORCID 0000-0003-1749-0408 0000-0003-1749-0408 researchmap permalink hide-tan-fk hide-tan-fk 著者名 Tanushi, Hideyuki
キーワード等	Research data article
	Abstract
	Number of citations
	Scientific Data
内容	Kai Naoto, Yoshihisa Tomoki, et al. Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data. Lecture Notes on Data Engineering and Communications Technologies 189, 1 (2023); https://doi.org/10.1007/978-3-031-46970-1_1.
抄録	With the trend of open science, efforts have been made to openly utilize research data. Considering the use of shared research data for interdisciplinary research, developing a researcher-friendly abstract writing method in different research fields is pertinent. In this study, we focus on abstracts from Scientific Data, a journal specializing in research data. We examine the influence of each part of speech on the utilization of research data through multiple regression analysis of the number of occurrences of the part of speech, the number of words and index-keywords in the abstract, and the number of citations research data article. Based on these results, we set the explanatory variables as the number of nouns, verbs, the other parts of speech, words, and index-keywords in the abstract. Thereafter, we developed a classifier to estimate the number of citations using machine learning. An analysis of the relationship between the number of citations and index keywords was also conducted.
会議情報	会議名 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2023) 回次 18 開催期間 November 8th to November 10th, 2023 開催会場 Daegu EXCO Convention Center 開催地 Daegu 開催国大韓民国
出版者	Springer Science and Business Media LLC
収録物名	Advances on P2P, Parallel, Grid, Cloud and Internet Computing (Lecture Notes on Data Engineering and Communications Technologies)
巻(号)	189
ページ	1-13
刊行年月	2023-10-29
言語	英語
ハンドルURL	https://hdl.handle.net/11094/93143
PISSN	23674512
eISSN	23674520
関連情報 (isVersionOf)	DOI (出版社版) https://doi.org/10.1007/978-3-031-46970-1_1
アクセス権	open access
出版タイプ	Accepted Manuscript
カテゴリ	会議発表論文 Conference Paper

資源タイプ	会議発表論文
ローカル資源タイプ	会議発表論文
DCMI資源タイプ	text
DCTERMS.bibliographicCitation	Advances on P2P, Parallel, Grid, Cloud and Internet Computing (Lecture Notes on Data Engineering and Communications Technologies). 2023, 189, p. 1-13
DC.title	Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data
DC.creator	Kai, Naoto
	Yoshihisa, Tomoki
	Shimbaru, Toshiki
	Yano, Hideto
	Tanushi, Hideyuki
DC.publisher	Springer Science and Business Media LLC
DC.language' scheme='DCTERMS.RFC1766	英語
DC.type' scheme='DCTERMS.DCMIType	text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2023-10-29
DC.identifier	https://doi.org/10.1007/978-3-031-46970-1_1
DC.subject	Research data article
	Abstract
	Number of citations
	Scientific Data
DC.description	Kai Naoto, Yoshihisa Tomoki, et al. Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data. Lecture Notes on Data Engineering and Communications Technologies 189, 1 (2023); https://doi.org/10.1007/978-3-031-46970-1_1.
DCTERMS.abstract	With the trend of open science, efforts have been made to openly utilize research data. Considering the use of shared research data for interdisciplinary research, developing a researcher-friendly abstract writing method in different research fields is pertinent. In this study, we focus on abstracts from Scientific Data, a journal specializing in research data. We examine the influence of each part of speech on the utilization of research data through multiple regression analysis of the number of occurrences of the part of speech, the number of words and index-keywords in the abstract, and the number of citations research data article. Based on these results, we set the explanatory variables as the number of nouns, verbs, the other parts of speech, words, and index-keywords in the abstract. Thereafter, we developed a classifier to estimate the number of citations using machine learning. An analysis of the relationship between the number of citations and index keywords was also conducted.
DC.format	93143
citation_title	Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data
citation_author	Kai, Naoto
	Yoshihisa, Tomoki
	Shimbaru, Toshiki
	Yano, Hideto
	Tanushi, Hideyuki
citation_publisher	Springer Science and Business Media LLC
citation_language	英語
citation_date	2023-10-29
citation_journal_title	Advances on P2P, Parallel, Grid, Cloud and Internet Computing (Lecture Notes on Data Engineering and Communications Technologies)
citation_volume	189
citation_firstpage	1
citation_lastpage	13
citation_doi	https://doi.org/10.1007/978-3-031-46970-1_1
citation_public_url	https://hdl.handle.net/11094/93143

Citation Estimation Method Using Abstracts of Research Data Articles: A Focus on Scientific Data

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