Analysing Author Self-Citations in Computer Science Publications

Tobias Milz; Christin Seifert

doi:10.1007/978-3-319-99133-7_24

Analysing Author Self-Citations in Computer Science Publications

Tobias Milz, Christin Seifert

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

6 Citations (Scopus)

230 Downloads (Pure)

Abstract

In scientific papers, citations refer to relevant previous work in order to underline the current line of argumentation, compare to other work and/or avoid repetition in writing. Self-citations, e.g. authors citing own previous work might have the same motivation but have also gained negative attention w.r.t. unjustified improvement of scientific performance indicators. Previous studies on self-citations do not provide a detailed analysis in the domain of computer science. In this work, we analyse the prevalence of self-citations in the DBLP, a digital library for computer science. We find, that approx. 10% of all citations are self-citations, while the rates vary with year after publication and the position of the author in the list as well as with the gender of the lead author. Further, we find that C-ranked venues have the highest incoming self-citation rate, while the outgoing rate is stable across all ranks.

Original language	English
Title of host publication	Database and Expert Systems Applications
Subtitle of host publication	DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings
Editors	Mourad Elloumi, Michael Granitzer, Abdelkader Hameurlain, Christin Seifert, Benno Stein, A. Min Tjoa, Roland Wagner
Publisher	Springer
Pages	289-300
Number of pages	12
ISBN (Electronic)	978-3-319-99133-7
ISBN (Print)	978-3-319-99132-0
DOIs	https://doi.org/10.1007/978-3-319-99133-7_24
Publication status	Published - 1 Jan 2018
Event	29th International Conference on Database and Expert Systems Applications, DEXA 2018 - Regensburg, Germany Duration: 3 Sept 2018 → 6 Sept 2018 Conference number: 29 http://www.dexa.org/dexa2018

Publication series

Name	Communications in Computer and Information Science
Volume	903
ISSN (Print)	1865-0929

Conference

Conference	29th International Conference on Database and Expert Systems Applications, DEXA 2018
Abbreviated title	DEXA
Country/Territory	Germany
City	Regensburg
Period	3/09/18 → 6/09/18
Internet address	http://www.dexa.org/dexa2018

Keywords

Analysis
CORE
Citations
DBLP
Self-citations

Access to Document

10.1007/978-3-319-99133-7_24

Milz2018_tir_selfcitations-in-cs_preprintAccepted author version, 401 KB

Cite this

Milz, T., & Seifert, C. (2018). Analysing Author Self-Citations in Computer Science Publications. In M. Elloumi, M. Granitzer, A. Hameurlain, C. Seifert, B. Stein, A. Min Tjoa, & R. Wagner (Eds.), Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings (pp. 289-300). (Communications in Computer and Information Science; Vol. 903). Springer. https://doi.org/10.1007/978-3-319-99133-7_24

Milz, Tobias ; Seifert, Christin. / Analysing Author Self-Citations in Computer Science Publications. Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings. editor / Mourad Elloumi ; Michael Granitzer ; Abdelkader Hameurlain ; Christin Seifert ; Benno Stein ; A. Min Tjoa ; Roland Wagner. Springer, 2018. pp. 289-300 (Communications in Computer and Information Science).

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abstract = "In scientific papers, citations refer to relevant previous work in order to underline the current line of argumentation, compare to other work and/or avoid repetition in writing. Self-citations, e.g. authors citing own previous work might have the same motivation but have also gained negative attention w.r.t. unjustified improvement of scientific performance indicators. Previous studies on self-citations do not provide a detailed analysis in the domain of computer science. In this work, we analyse the prevalence of self-citations in the DBLP, a digital library for computer science. We find, that approx. 10% of all citations are self-citations, while the rates vary with year after publication and the position of the author in the list as well as with the gender of the lead author. Further, we find that C-ranked venues have the highest incoming self-citation rate, while the outgoing rate is stable across all ranks.",

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Milz, T & Seifert, C 2018, Analysing Author Self-Citations in Computer Science Publications. in M Elloumi, M Granitzer, A Hameurlain, C Seifert, B Stein, A Min Tjoa & R Wagner (eds), Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings. Communications in Computer and Information Science, vol. 903, Springer, pp. 289-300, 29th International Conference on Database and Expert Systems Applications, DEXA 2018, Regensburg, Germany, 3/09/18. https://doi.org/10.1007/978-3-319-99133-7_24

Analysing Author Self-Citations in Computer Science Publications. / Milz, Tobias; Seifert, Christin.
Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings. ed. / Mourad Elloumi; Michael Granitzer; Abdelkader Hameurlain; Christin Seifert; Benno Stein; A. Min Tjoa; Roland Wagner. Springer, 2018. p. 289-300 (Communications in Computer and Information Science; Vol. 903).

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

TY - GEN

T1 - Analysing Author Self-Citations in Computer Science Publications

AU - Milz, Tobias

AU - Seifert, Christin

N1 - Conference code: 29

PY - 2018/1/1

Y1 - 2018/1/1

N2 - In scientific papers, citations refer to relevant previous work in order to underline the current line of argumentation, compare to other work and/or avoid repetition in writing. Self-citations, e.g. authors citing own previous work might have the same motivation but have also gained negative attention w.r.t. unjustified improvement of scientific performance indicators. Previous studies on self-citations do not provide a detailed analysis in the domain of computer science. In this work, we analyse the prevalence of self-citations in the DBLP, a digital library for computer science. We find, that approx. 10% of all citations are self-citations, while the rates vary with year after publication and the position of the author in the list as well as with the gender of the lead author. Further, we find that C-ranked venues have the highest incoming self-citation rate, while the outgoing rate is stable across all ranks.

AB - In scientific papers, citations refer to relevant previous work in order to underline the current line of argumentation, compare to other work and/or avoid repetition in writing. Self-citations, e.g. authors citing own previous work might have the same motivation but have also gained negative attention w.r.t. unjustified improvement of scientific performance indicators. Previous studies on self-citations do not provide a detailed analysis in the domain of computer science. In this work, we analyse the prevalence of self-citations in the DBLP, a digital library for computer science. We find, that approx. 10% of all citations are self-citations, while the rates vary with year after publication and the position of the author in the list as well as with the gender of the lead author. Further, we find that C-ranked venues have the highest incoming self-citation rate, while the outgoing rate is stable across all ranks.

KW - Analysis

KW - CORE

KW - Citations

KW - DBLP

KW - Self-citations

U2 - 10.1007/978-3-319-99133-7_24

DO - 10.1007/978-3-319-99133-7_24

M3 - Conference contribution

SN - 978-3-319-99132-0

T3 - Communications in Computer and Information Science

SP - 289

EP - 300

BT - Database and Expert Systems Applications

A2 - Elloumi, Mourad

A2 - Granitzer, Michael

A2 - Hameurlain, Abdelkader

A2 - Seifert, Christin

A2 - Stein, Benno

A2 - Min Tjoa, A.

A2 - Wagner, Roland

PB - Springer

T2 - 29th International Conference on Database and Expert Systems Applications, DEXA 2018

Y2 - 3 September 2018 through 6 September 2018

ER -

Milz T, Seifert C. Analysing Author Self-Citations in Computer Science Publications. In Elloumi M, Granitzer M, Hameurlain A, Seifert C, Stein B, Min Tjoa A, Wagner R, editors, Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings. Springer. 2018. p. 289-300. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-99133-7_24

Analysing Author Self-Citations in Computer Science Publications

Abstract

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Conference

Keywords

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