Clarivate Report Highlights Importance of Evolution in Data Categorization to Promote Responsible Research Metrics
Entitled "Data categorization: understanding choices and outcomes", the report from the
The team's research found that a categorization scheme informed by article metadata is stronger than one arranged by human concepts, e.g., those which are journal-based, top-down and use expert input to split domains into related sub-categories. Instead, a citation-based classification of articles and reviews progressively links individual elements into larger units with shared characteristics based on features in the underlying data. This innovative approach demonstrated in InCites™ Citation Topics more accurately represents microclusters, or specialties, provides more uniform content and improves citation normalization. It also gives opportunity for novel groups to appear that were not previously possible with journal-based schemes.
Apart from its wide range of data selections, tests and visualizations, InCites provides multiple choices of top-down data classifications and now also offers Citation Topics as a bottom-up citation-based classification. The current implementation of Citation Topics is composed of 10 macro topics, 326 meso topics and 2,444 micro topics, with monthly and annual updating built in which will allow it to evolve over time.
Notes for editors:
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