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: "competition and cooperation analysis for data sponsored market a network effects model"
  Abstract: The data sponsored scheme allows the content provider to cover parts of the cellular data costs for mobile users. Thus the content service becomes appealing to more users and potentially generates more profit gain to the content provider. In this paper, we consider a sponsored data market with a monopoly network service provider, a single content provider, and multiple users. In particular, we model the interactions of three entities as a two-stage Stackelberg game, where the service provider and content provider act as the leaders determining the pricing and sponsoring strategies, respectively, in the first stage, and the users act as the followers deciding on their data demand in the second stage. We investigate the mutual interaction of the service provider and content provider in two cases: (i) competitive case, where the content provider and service provider optimize their strategies separately and competitively, each aiming at maximizing the profit and revenue, respectively; and (ii) cooperative case, where the two providers jointly optimize their strategies, with the purpose of maximizing their aggregate profits. We analyze the sub-game perfect equilibrium in both cases. Via extensive simulations, we demonstrate that the network effects significantly improve the payoff of three entities in this market, i.e., utilities of users, the profit of content provider and the revenue of service provider. In addition, it is revealed that the cooperation between the two providers is the best choice for all three entities.

Connected through hyperedge HE-1 (induced by source paper "dynamic pricing for revenue maximization in mobile social data market with network effects"):
  with members:
    - "mobile data trading behavioral economics analysis and algorithm design"
    - "a socially aware incentive mechanism for mobile crowdsensing service market"
    - "exploiting social tie structure for cooperative wireless networking a social group utility maximization framework"
    - "price discrimination for energy trading in smart grid a game theoretic approach"
    - "time and location aware mobile data pricing"
    - "a survey of smart data pricing past proposals current plans and future trends"
    - "optimal pricing in networks with externalities"
    - "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach"

Connected through hyperedge HE-2 (induced by source paper "game theoretic analysis for joint sponsored and edge caching content service market"):
  with members:
    - "a socially aware incentive mechanism for mobile crowdsensing service market"
    - "joint optimization of data sponsoring and edge caching for mobile video delivery"
    - "caching in wireless small cell networks a storage bandwidth tradeoff"
    - "competitive caching of contents in 5g edge cloud networks"

Connected through hyperedge HE-3 (induced by source paper "a socially aware incentive mechanism for mobile crowdsensing service market"):
  with members:
    - "how peer effects influence energy consumption"
    - "crowdsourcing with tullock contests a new perspective"
    - "optimal pricing in networks with externalities"

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.GT(Computer Science and Game Theory)