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Beyond Citations: Corpus-based Methods for Detecting the Impact of Research Outcomes on Society
(2020)
This paper proposes, implements and evaluates a novel, corpus-based approach for identifying categories indicative of the impact of research via a deductive (top-down, from theory to data) and an inductive (bottom-up, from data to theory) approach. The resulting categorization schemes differ in substance. Research outcomes are typically assessed by using bibliometric methods, such as citation counts and patterns, or alternative metrics, such as references to research in the media. Shortcomings with these methods are their inability to identify impact of research beyond academia (bibliometrics) and considering text-based impact indicators beyond those that capture attention (altmetrics). We address these limitations by leveraging a mixed-methods approach for eliciting impact categories from experts, project personnel (deductive) and texts (inductive). Using these categories, we label a corpus of project reports per category schema, and apply supervised machine learning to infer these categories from project reports. The classification results show that we can predict deductively and inductively derived impact categories with 76.39% and 78.81% accuracy (F1-score), respectively. Our approach can complement solutions from bibliometrics and scientometrics for assessing the impact of research and studying the scope and types of advancements transferred from academia to society.
An approach to the unification of XML (Extensible Markup Language) documents with identical textual content and concurrent markup in the framework of XML-based multi-layer annotation is introduced. A Prolog program allows the possible relationships between element instances on two annotation layers that share PCDATA to be explored and also the computing of a target node hierarchy for a well-formed, merged XML document. Special attention is paid to identity conflicts between element instances, for which a default solution that takes into account metarelations that hold between element types on the different annotation layers is provided. In addition, rules can be specified by a user to prescribe how identity conflicts should be solved for certain element types.