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 "local community extraction in directed networks"):
  Abstract: Network is a simple but powerful representation of real-world complex systems. Network community analysis has become an invaluable tool to explore and reveal the internal organization of nodes. However, only a few methods were directly designed for community-detection in directed networks. In this article, we introduce the concept of local community structure in directed networks and provide a generic criterion to describe a local community with two properties. We further propose a stochastic optimization algorithm to rapidly detect a local community, which allows for uncovering the directional modular characteristics in directed networks. Numerical results show that the proposed method can resolve detailed local communities with directional information and provide more structural characteristics of directed networks than previous methods.

Includes members:
  Member "a neurodynamic framework for local community extraction in networks":
    also connected through other hyperedges:
      (none)
  Member "clustering and community detection in directed networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey of community search over big graphs")
  Member "scalable spectral algorithms for community detection in directed networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "detecting highly cyclic structure with complex eigenpairs")

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)