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Knoth, Petr and Herrmannova, Drahomira
(2014).
DOI: https://doi.org/10.1045/november2014-knoth
Abstract
We propose Semantometrics, a new class of metrics for evaluating research. As opposed to existing Bibliometrics,Webometrics, Altmetrics, etc., Semantometrics are not based on measuring the number of interactions in the scholarly communication network, but build on the premise that full-text is needed to assess the value of a publication. This paper presents the first Semantometric measure, which estimates the research contribution. We measure semantic similarity of publications connected in a citation network and use a simple formula to assess their contribution. We carry out a pilot study in which we test our approach on a small dataset and discuss the challenges in carrying out the analysis on existing citation datasets. The results suggest that semantic similarity measures can be utilised to provide meaningful information about the contribution of research papers that is not captured by traditional impact measures based purely on citations.
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About
- Item ORO ID
- 42527
- Item Type
- Journal Item
- ISSN
- 1082-9873
- Keywords
- citation analysis; research evaluation; semantic similarity; research publication datasets; semantometrics
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Research Group
-
Big Scientific Data and Text Analytics Group (BSDTAG)
Centre for Research in Computing (CRC) - Copyright Holders
- © 2014 Petr Knoth and Drahomira Herrmannova
- Depositing User
- Adam Jelley