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: "strategic resource allocation for competitive influence in social networks"
  Abstract: One of the main objectives of data mining is to help companies determine to which potential customers to market and how many resources to allocate to these potential customers. Most previous works on competitive influence in social networks focus on the first issue. In this work, our focus is on the second issue, i.e., we are interested on the competitive influence of marketing campaigns who need to simultaneously decide how many resources to allocate to their potential customers to advertise their products. Using results from game theory, we are able to completely characterize the optimal strategic resource allocation for the voter model of social networks and prove that the price of competition of this game is unbounded. This work is a step towards providing a solid foundation for marketing advertising in more general scenarios.

Connected through hyperedge HE-1 (induced by source paper "competitive influence maximization integrating budget allocation and seed selection"):
  with members:
    - "advertising competitions in social networks"
    - "from competition to complementarity comparative influence diffusion and maximization"
    - "influence maximization near optimal time complexity meets practical efficiency"
    - "maximizing social influence in nearly optimal time"

Connected through hyperedge HE-2 (induced by source paper "combinatorial bandits for sequential learning in colonel blotto games"):
  with members:
    - "colonel blotto and hide and seek games as path planning problems with side observations"
    - "regret in online combinatorial optimization"
    - "the on line shortest path problem under partial monitoring"

Connected through hyperedge HE-3 (induced by source paper "advertising competitions in social networks"):
  with members:
    - "competitive contagion in networks"

Connected through hyperedge HE-4 (induced by source paper "approximation algorithm for the binary preference capacitated selfish replication game and a tight bound on its price of anarchy"):
  with members:
    - "game theoretic analysis of the hegselmann krause model for opinion dynamics in finite dimensions"
    - "optimal versus nash equilibrium computation for networked resource allocation"
    - "on dynamics in selfish network creation"
    - "efficiency and nash equilibria in a scrip system for p2p networks"

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)