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 "communities as well separated subgraphs with cohesive cores identification of core periphery structures in link communities"):
  Abstract: Communities in networks are commonly considered as highly cohesive subgraphs which are well separated from the rest of the network. However, cohesion and separation often cannot be maximized at the same time, which is why a compromise is sought by some methods. When a compromise is not suitable for the problem to be solved it might be advantageous to separate the two criteria. In this paper, we explore such an approach by defining communities as well separated subgraphs which can have one or more cohesive cores surrounded by peripheries. We apply this idea to link communities and present an algorithm for constructing core-periphery structures in link communities and first test results.

Includes members:
  Member "memetic search for overlapping topics based on a local evaluation of link communities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how to interpret algorithmically constructed topical structures of research specialties a case study comparing an internal and an external mapping of the topical structure of invasion biology")
  Member "hyperbolae are no hyperbole modelling communities that are not cliques":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "what you will gain by rounding theory and algorithms for rounding rank")
  Member "identification of core periphery structure in networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "link prediction in networks with core fringe data")
  Member "overlapping community detection in networks the state of the art and comparative study":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "meta learning with relational information for short sequences")
  Member "defining and evaluating network communities based on ground truth":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "certified robustness of community detection against adversarial structural perturbation via randomized smoothing")
  Member "efficient and principled method for detecting communities in networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "exact blind community detection from signals on multiple graphs")
  Member "empirical comparison of algorithms for network community detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "certified robustness of community detection against adversarial structural perturbation via randomized smoothing")

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)