Abstract Network science is an interdisciplinary field that transcends traditional academic boundaries. However, a critical gap exists in understanding the epistemological fragmentation between empirical sociology and algorithmic science. This study addresses this by conducting a comparative bibliometric analysis of three leading journals: Social Networks, Network Science, and the Journal of Complex Networks. Beyond traditional mapping, our central contribution is the identification of ’topological bottlenecks’—seminal works that gatekeep interdisciplinary knowledge flow. We reveal a hierarchical ’scale-free’ structure that, while ensuring theoretical continuity, may inadvertently stifle the development of new frameworks needed for modern algorithmic complexities.
Pu Cui (Sat,) studied this question.
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