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 "fuzzy overlapping community quality metrics"):
  Abstract: Modularity is widely used to effectively measure the strength of the disjoint community structure found by community detection algorithms. Several overlapping extensions of modularity were proposed to measure the quality of overlapping community structure. However, all these extensions differ just in the way they define the belonging coefficient and belonging function. Yet, there is lack of systematic comparison of different extensions. To fill this gap, we overview overlapping extensions of modularity and generalize them with a uniform definition enabling application of different belonging coefficients and belonging functions to select the best. In addition, we extend localized modularity, modularity density, and eight local community quality metrics to enable their usages for overlapping communities. The experimental results on a large number of real networks and synthetic networks using overlapping extensions of modularity, overlapping modularity density, and local metrics show that the best results are obtained when the product of the belonging coefficients of two nodes is used as the belonging function. Moreover, the results may be used to guide researchers on which metrics to adopt when measuring the quality of overlapping community structure.

Includes members:
  Member "identifying robust communities and multi community nodes by combining top down and bottom up approaches to clustering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the intrinsic scale of networks is small")
  Member "a new metric for quality of network community structure":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a new measure of modularity density for community detection")
  Member "extension of modularity density for overlapping community structure":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a statistical density based analysis of graph clustering algorithm performance")
  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 "towards linear time overlapping community detection in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "community detection in node attributed social networks a survey")
  Member "defining and evaluating network communities based on ground truth":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "certified robustness of community detection against adversarial structural perturbation via randomized smoothing")
  Member "detect overlapping and hierarchical community structure in networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "ensemble based overlapping community detection using disjoint community structures")

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)