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 "distributed community detection via metastability of the 2 choices dynamics"):
  Abstract: We investigate the behavior of a simple majority dynamics on networks of agents whose interaction topology exhibits a community structure. By leveraging recent advancements in the analysis of dynamics, we prove that, when the states of the nodes are randomly initialized, the system rapidly and stably converges to a configuration in which the communities maintain internal consensus on different states. This is the first analytical result on the behavior of dynamics for non-consensus problems on non-complete topologies, based on the first symmetry-breaking analysis in such setting. Our result has several implications in different contexts in which dynamics are adopted for computational and biological modeling purposes. In the context of Label Propagation Algorithms, a class of widely used heuristics for community detection, it represents the first theoretical result on the behavior of a distributed label propagation algorithm with quasi-linear message complexity. In the context of evolutionary biology, dynamics such as the Moran process have been used to model the spread of mutations in genetic populations [Lieberman, Hauert, and Nowak 2005]; our result shows that, when the probability of adoption of a given mutation by a node of the evolutionary graph depends super-linearly on the frequency of the mutation in the neighborhood of the node and the underlying evolutionary graph exhibits a community structure, there is a non-negligible probability for species differentiation to occur.

Includes members:
  Member "pooling or sampling collective dynamics for electrical flow estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a distributed laplacian solver and its applications to electrical flow and random spanning tree computation")
  Member "phase transition of the 2 choices dynamics on core periphery networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "step by step community detection for volume regular graphs")
  Member "the ants problem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi round cooperative search games with multiple players")
  Member "limits for rumor spreading in stochastic populations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "noidy conmunixatipn on the convergence of the averaging population protocol")
  Member "ignore or comply on breaking symmetry in consensus":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "noidy conmunixatipn on the convergence of the averaging population protocol")
  Member "distributed graph clustering and sparsification":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "step by step community detection for volume regular graphs")
  Member "average whenever you meet opportunistic protocols for community detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "efficient distributed community detection in the stochastic block model")
  Member "a tight analysis of the parallel undecided state dynamics with two colors":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "consensus needs broadcast in noiseless models but can be exponentially easier in the presence of noise")

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)