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Title:Mining scholarly articles for citation contexts – A pilot study in information science domain
Author(s):Valencia, Kyndra R.; Lu, Ku
Subject(s):Citation contexts
Text mining
Coding scheme
Abstract:Citations are widely used to measure scholarly impact, reveal knowledge structure, and facilitate information retrieval. However, works are cited for different purposes in different contexts, for example, to provide a context for the current research, to explain concepts/theories, to describe methods/techniques, and to offer a critique. Understanding citation contexts (how citations are used) helps to devise more precise uses of citations. In this pilot study, we adopted a domain-specific approach to analyze citations of the articles from a major venue in information science. A coding scheme is developed to categorize different uses of citations within the domain. Initial results show some promises. Future studies will increase the sample size and further explore automated methods, such as supervised machine learning, for this problem.
Issue Date:2017
Publisher:iSchools
Citation Info:Valencia, K. R., & Lu, K. (2017). Mining Scholarly Articles for Citation Contexts – A Pilot Study in Information Science Domain. In iConference 2017 Proceedings (pp. 667-671). https://doi.org/10.9776/17314
Series/Report:iConference 2017 Proceedings
Genre:Conference Poster
Type:Text
Language:English
URI:http://hdl.handle.net/2142/96694
DOI:https://doi.org/10.9776/17314
Rights Information:Copyright 2017 Kyndra R. Valencia and Ku Lu
Date Available in IDEALS:2017-07-27


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