human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on influence stable behavior and the most influential individuals in networks a game theoretic approach"):
  Abstract: We introduce a new approach to the study of influence in strategic settings where the action of an individual depends on that of others in a network-structured way. We propose network influence games as a game-theoretic model of the behavior of a large but finite networked population. In particular, we study an instance we call linear-influence games that allows both positive and negative influence factors, permitting reversals in behavioral choices. We embrace pure-strategy Nash equilibrium, an important solution concept in non-cooperative game theory, to formally define the stable outcomes of a network influence game and to predict potential outcomes without explicitly considering intricate dynamics. We address an important problem in network influence, the identification of the most influential individuals, and approach it algorithmically using pure-strategy Nash-equilibria computation. Computationally, we provide (a) complexity characterizations of various problems on linear-influence games; (b) efficient algorithms for several special cases and heuristics for hard cases; and (c) approximation algorithms, with provable guarantees, for the problem of identifying the most influential individuals. Experimentally, we evaluate our approach using both synthetic network influence games and real-world settings of general interest, each corresponding to a separate branch of the U.S. Government. Mathematically, we connect linear-influence games to important models in game theory: potential and polymatrix games.

Includes members:
  Member "graphical models for game theory":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "complexity theory game theory and economics the barbados lectures")
  Member "power indices of influence games and new centrality measures for social networks":
    also connected through other hyperedges:
      (none)
  Member "efficient computation of the shapley value for game theoretic network centrality":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning to resolve alliance dilemmas in many player zero sum games")
  Member "learning the structure and parameters of large population graphical games from behavioral data":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "strategic prediction with latent aggregative games")
  Member "competitive contagion in networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximation algorithms for coordinating ad campaigns on social networks")
  Member "pure nash equilibria hard and easy games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "graphical one sided markets")

Question: Please tell me which class the source paper 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)