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Feature Analysis of Research Metrics Systems


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Feature Analysis of Research Metrics Systems

Authors: Aarthy Nagarajan, Mojisola Erdt, Yin-Leng Theng

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Published in: Technology
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Feature Analysis of Research Metrics Systems

  1. 1. Feature Analysis of Research Metrics Systems Abstract Feature Analysis of Systems Identify presence of Key Features Limitations Inter-Rater Reliability Method (IRR) Unsure as per one or both coders; 0.5 Present; 2 Not present as per one of the coders; 1 0 5 10 15 20 25 30 35 Verification of metrics provided DOI or URL provided to the research work ORCID DOIS Google Scholar ID ResearcherID ScopusID Offers own API Bookmarklet Plugins Profile/ Logo link to profile embedding Supports Search Supports Sorting Supports Filtering Allows import Allows export RSS feed Supports article sharing to third party platform Novel in-house metrics offered Publically known factors contributing to metric The context of the metrics is provided Artifact level metrics Article level metrics Journal level metrics Author/ Researcher level metrics Institutional/ Organisational level metrics Country level Registration Free access Subscription/License Needed Time-series (Temporal) analysis Spatial analysis Cross-metric Analysis Informational details shown Google Scholar Citations WoS Citations Scopus Citations H-index Impact Factor Number of publication/articles Recommendations Dashboard provided No of full text downloads No. of views score Twitter Facebook Mendeley DataQualityUsercontrol&EmbeddingMetricsrelated User AccessVisualizationBibliometricSources User- friendl y interfa ceAltmetricSources Coverage per system Features ImpactStory KUDOS Aminer Publish or Perish Figshare ORCID Mendeley Plum Analytics Scholarometer ResearchGate Academia.Edu Elsevier ScienceDirect Elsevier Scopus Springer (Springer Nature) Emerald Insight Wiley Online Library Inter-Rater Reliability was found to be the highest (κ = 0.675, p<0.001) for features related to altmetric sources Inter-Rater Reliability was found to be the lowest (κ = 0.406, p<0.001) for features related to metric validation User-control & embedding features are covered by maximum number of systems Visualization is the least covered feature Mendeley and Elsevier Scopus show presence of maximum number of features Since the advent of “Altmetrics”, the number of research metrics systems that have been developed has increased. As part of this study, we have analysed the presence of some prominent features in 10 altmetrics systems, 2 academic social networking systems, and 6 other systems covering digital libraries, databases and publisher systems. We considered a total of 48 individual features under 14 broad categories for the analysis. We found that user-control and embedding features were present in most of the systems, whereas visualization features were present in few of the systems. The results of this study give insights into features that could be improved and developed in future. Authors Aarthy Nagarajan Dr Mojisola Erdt Prof Theng Yin-Leng Research Engineer Research Fellow Professor Nanyang Technological University Nanyang Technological University Nanyang Technological University This research is supported by the National Research Foundation, Prime Minister's Office, Singapore under its Science of Research, Innovation and Enterprise programme (SRIE Award No. NRF2014-NRF-SRIE001-019). Any opinions, findings, conclusions and/or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Research Foundation Singapore.