Citation Proximity-Context Analysis for Interdisciplinary Common Knowledge Discovery

However, identifying and elucidating common knowledge across disciplines can enhance cross-field visibility, reduce redundant research efforts, as well as promote the diffusion and application of knowledge across domains. Therefore, this study proposes a methodology that leverages citation context to identify common knowledge among disciplines.

By analyzing co-cited patterns in citation contexts drawn from existing cases of interdisciplinary common knowledge and extracting these patterns from a large-scale dataset, we designed evaluation metrics that consider commonality, interdisciplinarity, and novelty to identify valid, novel, potentially useful, and understandable interdisciplinary common knowledge. Eventually, 1,044 candidate pairs of interdisciplinary knowledge were identified.