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 "fast change point detection on dynamic social networks"):
  Abstract: A number of real world problems in many domains (e.g. sociology, biology, political science and communication networks) can be modeled as dynamic networks with nodes representing entities of interest and edges representing interactions among the entities at different points in time. A common representation for such models is the snapshot model - where a network is defined at logical time-stamps. An important problem under this model is change point detection. In this work we devise an effective and efficient three-step-approach for detecting change points in dynamic networks under the snapshot model. Our algorithm achieves up to 9X speedup over the state-of-the-art while improving quality on both synthetic and real world networks.

Includes members:
  Member "random graph models for dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "bayesian graph convolutional neural networks using node copying")
  Member "modelling sequences and temporal networks with dynamic community structures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "computational human dynamics")
  Member "detecting weak changes in dynamic events over networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fake news mitigation via point process based intervention")
  Member "detecting change points in the large scale structure of evolving networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "change detection in dynamic attributed networks")
  Member "multi level anomaly detection on time varying graph data":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "quantifiable comparable evaluations of cyber defensive capabilities a survey novel unified approach")
  Member "fast generation of large scale social networks with clustering":
    also connected through other hyperedges:
      (none)
  Member "community structure and scale free collections of erdős renyi graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "artificial benchmark for community detection abcd fast random graph model with community structure")
  Member "netsimile a scalable approach to size independent network similarity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "unicorn runtime provenance based detector for advanced persistent threats")

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)