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: "optimal pricing in networks with externalities"
  Abstract: We study the optimal pricing strategies of a monopolist selling a divisible good (service) to consumers that are embedded in a social network. A key feature of our model is that consumers experience a (positive) local network effect. In particular, each consumer's usage level depends directly on the usage of her neighbors in the social network structure. Thus, the monopolist's optimal pricing strategy may involve offering discounts to certain agents, who have a central position in the underlying network. #R##N#First, we consider a setting where the monopolist can offer individualized prices and derive an explicit characterization of the optimal price for each consumer as a function of her network position. In particular, we show that it is optimal for the monopolist to charge each agent a price that is proportional to her Bonacich centrality in the social network. In the second part of the paper, we discuss the optimal strategy of a monopolist that can only choose a single uniform price for the good and derive an algorithm polynomial in the number of agents to compute such a price. Thirdly, we assume that the monopolist can offer the good in two prices, full and discounted, and study the problem of determining which set of consumers should be given the discount. We show that the problem is NP-hard, however we provide an explicit characterization of the set of agents that should be offered the discounted price. Next, we describe an approximation algorithm for finding the optimal set of agents. We show that if the profit is nonnegative under any feasible price allocation, the algorithm guarantees at least 88% of the optimal profit. Finally, we highlight the value of network information by comparing the profits of a monopolist that does not take into account the network effects when choosing her pricing policy to those of a monopolist that uses this information optimally.

Connected through hyperedge HE-1 (induced by source paper "pricing in resource allocation games based on lagrangean duality and convexification"):
  with members:
    - "nash and wardrop equilibria in aggregative games with coupling constraints"
    - "sensitivity analysis for convex separable optimization over integral polymatroids"
    - "totally unimodular congestion games"
    - "combinatorial walrasian equilibrium"
    - "polyhedral clinching auctions and the adwords polytope"
    - "congestion games with variable demands"

Connected through hyperedge HE-2 (induced by source paper "selling a single item with negative externalities"):
  with members:
    - "dancing pigs or externalities measuring the rationality of security decisions"
    - "approximate revenue maximization with multiple items"
    - "pricing public goods for private sale"
    - "algorithmic pricing via virtual valuations"

Connected through hyperedge HE-3 (induced by source paper "competitive contagion with sparse seeding"):
  with members:
    - "competitive diffusion in social networks quality or seeding"
    - "competitive contagion in networks"

Connected through hyperedge HE-4 (induced by source paper "pricing in resource allocation games based on duality gaps"):
  with members:
    - "network congestion control with markovian multipath routing"

Connected through hyperedge HE-5 (induced by source paper "blind community detection from low rank excitations of a graph filter"):
  with members:
    - "latent agents in networks estimation and pricing"
    - "graph learning from filtered signals graph system and diffusion kernel identification"
    - "blind identification of graph filters"
    - "autoregressive moving average graph filtering"
    - "reconstruction of graph signals through percolation from seeding nodes"
    - "network topology inference from spectral templates"
    - "active sensing of social networks"
    - "learning sparse graphs under smoothness prior"

Connected through hyperedge HE-6 (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"
    - "competition and cooperation analysis for data sponsored market a network effects model"
    - "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"
    - "price based resource allocation for spectrum sharing femtocell networks a stackelberg game approach"

Connected through hyperedge HE-7 (induced by source paper "a stackelberg game approach towards socially aware incentive mechanisms for mobile crowdsensing online report"):
  with members:
    - "a socially aware incentive mechanism for mobile crowdsensing service market"
    - "dynamic routing for social information sharing"
    - "crowdsourcing with tullock contests a new perspective"
    - "optimal pricing in social networks with incomplete information"

Connected through hyperedge HE-8 (induced by source paper "optimal pricing for a peer to peer sharing platform under network externalities"):
  with members:
    - "mobile social services with network externality from separate pricing to bundled pricing"
    - "scalable mobile crowdsensing via peer to peer data sharing"
    - "dynamic routing for social information sharing"

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)