human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "network models that reflect multiplex dynamics"
  Abstract: Many of the systems that are traditionally analyzed as complex networks have natural interpretations as multiplex structures. While these formulations retain more information than standard network models, there is not yet a fully developed theory for computing network metrics and statistics on these objects. As many of the structural representations associated to these models can distort the underlying characteristics of dynamical process, we introduce an algebraic method for modeling arbitrary dynamics on multiplex networks. Since several network metrics are based on generalized notions of dynamical transfer, we can use this framework to extend many of the standard network metrics to multiplex structures in a consistent fashion.

Connected through hyperedge HE-1 (induced by source paper "spectral clustering methods for multiplex networks"):
  with members:
    - "geometric multiscale community detection markov stability and vector partitioning"
    - "community detection link prediction and layer interdependence in multilayer networks"
    - "detectability of small communities in multilayer and temporal networks eigenvector localization layer aggregation and time series discretization"
    - "non negative matrix factorizations for multiplex network analysis"
    - "generative benchmark models for mesoscale structures in multilayer networks"
    - "general tensor spectral co clustering for higher order data"
    - "a new framework for dynamical models on multiplex networks"
    - "a local perspective on community structure in multilayer networks"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SI(Social and Information Networks)