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: "social learning with coordination motives"
  Abstract: The theoretical study of social learning typically assumes that each agent's action affects only her own payoff. In this paper, I present a model in which agents' actions directly affect the payoffs of other agents. On a discrete time line, there is a community containing a random number of agents in each period. Before each agent needs to take an action, the community receives a private signal about the underlying state of the world and may observe some past actions in previous communities. An agent's payoff is higher if her action matches the state or if more agents take the same action as hers. I analyze two observation structures: exogenous observation and costly strategic observation. In both cases, coordination motives enhance social learning in the sense that agents take the correct action with significantly higher probability when the community size is greater than a threshold. In particular, this probability reaches one (asymptotic learning) with unbounded private beliefs and can be arbitrarily close to one with bounded private beliefs. I then discuss the issue of multiple equilibria and use risk dominance as a criterion for equilibrium selection. I find that in the selected equilibria, the community size has no effect on learning under exogenous observation, facilitates learning under endogenous observation and unbounded private beliefs, and either helps or hinders learning under endogenous observation and bounded private beliefs.

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)