human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "spectral clustering methods for multiplex networks"):
  Abstract: Multiplex networks offer an important tool for the study of complex systems and extending techniques originally designed for single--layer networks is an important area of study. One of the most important methods for analyzing networks is clustering the nodes into communities that represent common connectivity patterns. In this paper we extend spectral clustering to multiplex structures and discuss some of the difficulties that arise in attempting to define a natural generalization. In order to analyze our approach, we describe three simple, synthetic multiplex networks and compare the performance of different multiplex models. Our results suggest that a dynamically motivated model is more successful than a structurally motivated model in discovering the appropriate communities.

Includes members:
  Member "geometric multiscale community detection markov stability and vector partitioning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "semi supervised classification on graphs using explicit diffusion dynamics")
  Member "community detection link prediction and layer interdependence in multilayer networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "community detection on mixture multi layer networks via regularized tensor decomposition")
  Member "detectability of small communities in multilayer and temporal networks eigenvector localization layer aggregation and time series discretization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the ground truth about metadata and community detection in networks")
  Member "non negative matrix factorizations for multiplex network analysis":
    also connected through other hyperedges:
      (none)
  Member "generative benchmark models for mesoscale structures in multilayer networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "nonlinearity networks a 2020 vision")
  Member "general tensor spectral co clustering for higher order data":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "landing probabilities of random walks for seed set expansion in hypergraphs")
  Member "a new framework for dynamical models on multiplex networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "supracentrality analysis of temporal networks with directed interlayer coupling")
  Member "network models that reflect multiplex dynamics":
    also connected through other hyperedges:
      (none)

Question: Please tell me which class the source paper 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)