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| Academic Paper Profiling Based on CCA: A Theoretical Framework and Empirical Study |
| Wang Xinyue, Zhao Danqun |
| Department of Information Management, Peking University, Beijing 100871 |
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Abstract Academic paper profiling can be categorized into two types: static profiling based on full text and dynamic profiling based on its citation corpus. This study focuses on the latter, and introduces citation content analysis (CCA) method to dynamically characterize a paper’s academic impact by collecting and analyzing peer-cited texts after its publication. Such dynamic profile provides critical support for downstream tasks such as paper evaluation and academic resource retrieval and recommendation. First, a three-dimensional framework profiling paper’s academic impact— “impact power, impact field & impact path” (Im-PFP) is developed through theoretical analysis. Then, an empirical study was conducted using a self-compiled citation corpus, with a single highly cited paper— “Co-citation in the scientific literature: a new measure of the relationship between two documents” (Small, 1973) — as a case study. The empirical result validates the universality and practical value of the Im-PFP framework proposed in this study, which can be extended to profiling studies of single or multiple highly cited papers across different disciplines. Profiling outcomes enable both the classification of an academic paper’s lifecycle stages and the analysis of temporal evolution of its impact power, impact field and impact path.
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Received: 05 June 2025
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