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 "a scalable generative graph model with community structure"):
  Abstract: Network data is ubiquitous and growing, yet we lack realistic generative network models that can be calibrated to match real-world data. The recently proposed block two-level Erdos--Renyi (BTER) model can be tuned to capture two fundamental properties: degree distribution and clustering coefficients. The latter is particularly important for reproducing graphs with community structure, such as social networks. In this paper, we compare BTER to other scalable models and show that it gives a better fit to real data. We provide a scalable implementation that requires only $O(d_{\rm max})$ storage, where $d_{\rm max}$ is the maximum number of neighbors for a single node. The generator is trivially parallelizable, and we show results for a Hadoop MapReduce implementation for modeling a real-world Web graph with over 4.6 billion edges. We propose that the BTER model can be used as a graph generator for benchmarking purposes and provide idealized degree distributions and clustering coefficient profiles that can b...

Includes members:
  Member "counting triangles in massive graphs with mapreduce":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parallel algorithms for small subgraph counting")
  Member "an in depth analysis of stochastic kronecker graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances in scalable network generation")
  Member "decompositions of triangle dense graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mrattractor detecting communities from large scale graphs")
  Member "triadic measures on graphs the power of wedge sampling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parallel algorithms for small subgraph counting")
  Member "community structure and scale free collections of erdős renyi graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "artificial benchmark for community detection abcd fast random graph model with community structure")
  Member "a scalable null model for directed graphs matching all degree distributions in out and reciprocal":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recent advances in scalable network generation")
  Member "revisiting degree distribution models for social graph analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "constructing and sampling graphs with a prescribed joint degree distribution")
  Member "the similarity between stochastic kronecker and chung lu graph models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "signed network modeling based on structural balance theory")

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)