[Purpose/Significance] This paper constructs an interdisciplinarity measurement system based on Self-established Interdisciplinary Programs for Graduate Degrees (SIPs) in Chinese universities. On this basis, this paper aims to explore the overall construction characteristics of SIPs and specific combination patterns of the relevant Tier-2 Disciplinary Programs (T2Ps), and provide references for interdisciplinary construction and talent cultivation. [Method/Process] From the perspective of complex network analysis, several networks were constructed: the co-occurrence network and hypergraph of T2Ps; the coupling network of SIPs; and the three-mode network “SIPs-T2Ps-T1Ps (Tier-1 Disciplinary Programs)”. This paper uses the structural characteristics of the four types of networks and network visualization techniques to present the interdisciplinary features of SIPs, and constructs a measurement system that includes indicators such as cohesion and diversity. Comprehensive analyses were conducted by applying cohesion, diversity, and integration indicators to measure and analyze these networks and their clustering results. Among them, the co-occurrence network of T2Ps can reveal binary associations among T2Ps, while the hypergraph more accurately represents the interdisciplinary relationships among multiple T2Ps. The coupling network of SIPs, through community detection algorithms, helps obtain the overall research topics of SIPs. The “SIPs-T2Ps-T1Ps” three-mode network focuses on the three currently most popular types of SIPs and comparatively explores the knowledge integration characteristics formed by typical current SIPs from four aspects: the variety of T2Ps and T1Ps, the balance of T1Ps, and the disparity of T2Ps. [Result/Conclusion] T2Ps such as Computer Science & Technology and Management Science & Engineering lead prominently in both the breadth and strength of interdisciplinary engagement. The T2Ps involved in SIPs exhibit distinct integration features, such as medical-medicine fusion, medicine-biology integration, engineering-engineering crossover, and management interpenetration. The establishment of SIPs aligns with scientific research frontiers, national science & technology development strategies, and socio-economic needs, covering fields such as Artificial Intelligence (AI), Data Science, and Security. Security-focused SIPs involve the widest range of disciplines, evenly integrating specialized knowledge from different T2Ps, which also exhibit relatively pronounced differentiation among themselves. Finally, this paper discusses the development pathway for SIPs and their contributions to interdisciplinary talent cultivation, institutional restructuring, and organizational construction. [Innovation/Value] Building on previous studies, this paper adds the analytical perspectives of a hypergraph of T2Ps, a coupling network of SIPs, and a three-mode network of “SIPs-T2Ps-T1Ps”, thereby measuring more comprehensively and precisely the interdisciplinary characteristics exhibited by SIPs. In addition, this paper selects the latest catalog of SIPs and measures interdisciplinarity from the top-level design perspective of disciplinary construction, compensating for the shortcomings of previous interdisciplinarity measurement studies, which overemphasize measurement entities located in the mid- and lower reaches of the academic ecosystem, such as academic journals and funding project applications. [Insufficient/Improvement] In the measurement process, no conceptual, methodological, or instrumental distinctions were made regarding the interdisciplinary relationships among T2Ps, and no case analysis was conducted in conjunction with universities’ actual disciplinary construction, personnel composition, or organizational setup.
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