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 "adapting stochastic block models to power law degree distributions"):
  Abstract: Stochastic block models (SBMs) have been playing an important role in modeling clusters or community structures of network data. But, it is incapable of handling several complex features ubiquitously exhibited in real-world networks, one of which is the power-law degree characteristic. To this end, we propose a new variant of SBM, termed power-law degree SBM (PLD-SBM), by introducing degree decay variables to explicitly encode the varying degree distribution over all nodes. With an exponential prior, it is proved that PLD-SBM approximately preserves the scale-free feature in real networks. In addition, from the inference of variational E-Step, PLD-SBM is indeed to correct the bias inherited in SBM with the introduced degree decay factors. Furthermore, experiments conducted on both synthetic networks and two real-world datasets including Adolescent Health Data and the political blogs network verify the effectiveness of the proposed model in terms of cluster prediction accuracies.

Includes members:
  Member "estimating the number of communities in a network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mean field theory of graph neural networks in graph partitioning")
  Member "role discovery in networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep learning for learning graph representations")
  Member "model selection for degree corrected block models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "role detection in bicycle sharing networks using multilayer stochastic block models")
  Member "dynamic infinite mixed membership stochastic blockmodel":
    also connected through other hyperedges:
      (none)
  Member "the nonparametric metadata dependent relational model":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "struct mmsb mixed membership stochastic blockmodels with interpretable structured priors")
  Member "oriented and degree generated block models generating and inferring communities with inhomogeneous degree distributions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "role detection in bicycle sharing networks using multilayer stochastic block models")
  Member "a tutorial on spectral clustering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "approximating spectral clustering via sampling a review")

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)