Content-based citation analysis: The next generation of citation analysis

Abstract

Traditional citation analysis has been widely applied to detect patterns of scientific collaboration, map the landscapes of scholarly disciplines, assess the impact of research outputs, and observe knowledge transfer across domains. It is, however limited, as it assumes all citations are of similar value and weights each equally. Content-based citation analysis (CCA) addresses a citation’s value by interpreting each based on their contexts at both syntactic and semantic level. This paper provides a comprehensive overview of CAA research in terms of its theoretical foundations, methodical approaches, and example applications. In addition, we highlight how increased computational capabilities and publicly available full-text resources have opened this area of research to vast possibilities, which enable deeper of citation analysis, more accurate citation prediction, and increased knowledge discovery.

DOI: 10.1002/asi.23256

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Citations per Year

Citation Velocity: 16

Averaging 16 citations per year over the last 3 years.

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Cite this paper

@article{Ding2014ContentbasedCA, title={Content-based citation analysis: The next generation of citation analysis}, author={Ying Ding and Guo Zhang and Tamy Chambers and Min Song and Xiaolong Wang and ChengXiang Zhai}, journal={JASIST}, year={2014}, volume={65}, pages={1820-1833} }