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 "role detection in bicycle sharing networks using multilayer stochastic block models"):
  Abstract: Urban spatial networks are complex systems with interdependent roles of neighborhoods and methods of transportation between them. In this paper, we classify docking stations in bicycle-sharing networks to gain insight into the spatial delineations of three major United States cities from human mobility dynamics. We propose novel time-dependent stochastic block models, with degree-heterogeneous blocks and either mixed or discrete block membership, which (1) detect the roles served by bicycle-sharing docking stations and (2) describe the traffic within and between blocks of stations over the course of a day. Our models produce concise descriptions of daily bicycle-sharing usage patterns in urban environments. They successfully uncover work and home districts, and they also reveal dynamics of such districts that are particular to each city. When we look for more than two roles, we uncover blocks with expected uses, such as leisure activity, as well as previously unknown structures. Our time-dependent SBMs also reveal how the functional roles of bicycle-sharing stations are influenced by surrounding public transportation infrastructure. Our work has direct application to the design and maintenance of bicycle-sharing systems, and it can be applied more broadly to community detection in temporal and multilayer networks.

Includes members:
  Member "relating modularity maximization and stochastic block models in multilayer networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "supracentrality analysis of temporal networks with directed interlayer coupling")
  Member "community discovery in dynamic networks a survey":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey of community search over big graphs")
  Member "a multi scale analysis of 27 000 urban street networks every us city town urbanized area and zillow neighborhood":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an unsupervised approach to geographical knowledge discovery using street level and street network images")
  Member "random graph models for dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bayesian graph convolutional neural networks using node copying")
  Member "the ground truth about metadata and community detection in networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parameterized objectives and algorithms for clustering bipartite graphs and hypergraphs")
  Member "a framework for the construction of generative models for mesoscale structure in multilayer networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "nonlinearity networks a 2020 vision")
  Member "clustering network layers with the strata multilayer stochastic block model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hyperbolic multiplex network embedding with maps of random walk")
  Member "equivalence between modularity optimization and maximum likelihood methods for community detection":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mga momentum gradient attack on network")

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)