Altmetrics and Citation Counts: An Empirical Analysis of the Computer Science Domain

Yusra Shakeel, Rand Alchokr, Jacob Krüger, Thomas Leich, Gunter Saake

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

8 Citaten (Scopus)

Samenvatting

Background. Researchers, funding agencies, and institutions involve bibliographic data to assess the impact or reputation of papers, publication venues, researchers, and institutions. Particularly citation counts, and metrics that build on these (e.g., impact factor, h-index), are widely used, despite extensive and rightful criticism regarding, for instance, their meaning, value, and comparability. Moreover, such metrics require time to accumulate and do not represent the scientific impact outside of academia, for instance, on industry. To overcome such limitations, researchers investigate and propose altmetrics to complement or provide a more meaningful alternative to traditional metrics. Altmetrics are based on user interactions in the internet and especially social-media platforms, promising a faster accumulation and to represent scientific impact on other parts of society. Aim. In this paper, we complement current research by studying the altmetrics of 18,360 papers published at 16 publication venues of the computer science domain. Method. Namely, we conducted an empirical study to understand whether altmetrics correlate with citation counts and how they have evolved over time. Results. Our results help understand how altmetrics can complement citation counts, and which represent proxy metrics that indicate the immediate impact of a paper as well as future citations. We discuss our results extensively to reflect on the limitations and criticism on such metrics. Conclusion. Our findings suggest that altmetrics can be helpful to complement citation metrics, potentially providing a better picture of overall scientific impact and reducing potential biases of focusing solely on citations.
Originele taal-2Engels
TitelJCDL 2022 - Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2022
UitgeverijAssociation for Computing Machinery, Inc
Pagina's17
Aantal pagina's1
ISBN van elektronische versie9781450393454
DOI's
StatusGepubliceerd - 20 jun. 2022

Bibliografische nota

DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

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