Abstract
This paper proposes Conceptual Knowledge Entropy, a network-based metric for quantifying the convergence of conceptual relationships in scholarly literature. Grounded in the entropy literature, Conceptual Knowledge Entropy assesses the probability distribution of relationship paths to a dependent concept, with higher values indicating greater theoretical agreement. We also introduce Conceptual Knowledge Entropy Sensitivity to examine the influence of individual publications and antecedents on conceptual convergence. We demonstrate the application of this measure using the MISQ Curation dataset. This study contributes to the development of quantitative measures for evaluating scholarly knowledge. We discuss and outline future research directions to refine and extend the application of this measure.
Recommended Citation
Song, Yuanyuan; Watson, Richard; Xie, Yancong; and Zhao, Xia, "An Entropy Measure of Knowledge Evolution" (2025). ACIS 2025 Proceedings. 27.
https://aisel.aisnet.org/acis2025/27