human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "how agreement and disagreement evolve over random dynamic networks"
  Abstract: The dynamics of an agreement protocol interacting with a disagreement process over a common random network is considered. The model can represent the spreading of true and false information over a communication network, the propagation of faults in a large-scale control system, or the development of trust and mistrust in a society. At each time instance and with a given probability, a pair of network nodes are selected to interact. At random each of the nodes then updates its state towards the state of the other node (attraction), away from the other node (repulsion), or sticks to its current state (neglect). Agreement convergence and disagreement divergence results are obtained for various strengths of the updates for both symmetric and asymmetric update rules. Impossibility theorems show that a specific level of attraction is required for almost sure asymptotic agreement and a specific level of repulsion is required for almost sure asymptotic disagreement. A series of sufficient and/or necessary conditions are then established for agreement convergence or disagreement divergence. In particular, under symmetric updates, a critical convergence measure in the attraction and repulsion update strength is found, in the sense that the asymptotic property of the network state evolution transits from agreement convergence to disagreement divergence when this measure goes from negative to positive. The result can be interpreted as a tight bound on how much bad action needs to be injected in a dynamic network in order to consistently steer its overall behavior away from consensus.

Connected through hyperedge HE-1 (induced by source paper "opinion dynamics on correlated subjects in social networks"):
  with members:
    - "belief dynamics in social networks a fluid based analysis"
    - "novel multidimensional models of opinion dynamics in social networks"
    - "ergodic randomized algorithms and dynamics over networks"
    - "on the convergence of the hegselmann krause system"

Connected through hyperedge HE-2 (induced by source paper "dynamics of opinions with social biases"):
  with members:
    - "consensus over random graph processes network borel cantelli lemmas for almost sure convergence"
    - "the evolution of beliefs over signed social networks"
    - "opinion fluctuations and disagreement in social networks"
    - "biased assimilation homophily and the dynamics of polarization"
    - "how bad is forming your own opinion"

Connected through hyperedge HE-3 (induced by source paper "belief dynamics in social networks a fluid based analysis"):
  with members:
    - "consensus convergence with stochastic effects"
    - "bounded confidence opinion dynamics in a social network of bayesian decision makers"
    - "ergodic randomized algorithms and dynamics over networks"
    - "on the convergence of the hegselmann krause system"

Connected through hyperedge HE-4 (induced by source paper "a tutorial on modeling and analysis of dynamic social networks part i"):
  with members:
    - "on the analysis of the degroot friedkin model with dynamic relative interaction matrices"
    - "opinion evolution in time varying social influence networks with prejudiced agents"
    - "differential inequalities in multi agent coordination and opinion dynamics modeling"
    - "distributed algorithms for computation of centrality measures in complex networks"
    - "novel multidimensional models of opinion dynamics in social networks"
    - "open multi agent systems gossiping with random arrivals and departures"
    - "active sensing of social networks"
    - "structural balance and opinion separation in trust mistrust social networks"

Connected through hyperedge HE-5 (induced by source paper "dynamics over signed networks"):
  with members:
    - "structural balance and opinion separation in trust mistrust social networks"
    - "opinion dynamics in social networks with hostile camps consensus vs polarization"
    - "consensus over random graph processes network borel cantelli lemmas for almost sure convergence"
    - "convergence and state reconstruction of time varying multi agent systems from complete observability theory"
    - "the evolution of beliefs over signed social networks"
    - "distributed consensus algorithms in sensor networks quantized data and random link failures"

Connected through hyperedge HE-6 (induced by source paper "persistent flows and non reciprocal interactions in deterministic networks"):
  with members:
    - "structural balance and opinion separation in trust mistrust social networks"
    - "consensus over random graph processes network borel cantelli lemmas for almost sure convergence"
    - "continuous time consensus under non instantaneous reciprocity"
    - "convergence of type symmetric and cut balanced consensus seeking systems extended version"
    - "the role of persistent graphs in the agreement seeking of social networks"

Connected through hyperedge HE-7 (induced by source paper "sampled data consensus over random networks"):
  with members:
    - "opinion fluctuations and disagreement in social networks"
    - "sensor networks with random links topology design for distributed consensus"
    - "distributed consensus algorithms in sensor networks quantized data and random link failures"

Connected through hyperedge HE-8 (induced by source paper "convergence and state reconstruction of time varying multi agent systems from complete observability theory"):
  with members:
    - "the evolution of beliefs over signed social networks"
    - "gossip algorithms for distributed signal processing"
    - "distributed parameter estimation in sensor networks nonlinear observation models and imperfect communication"

Question: Please tell me which class the center node 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)