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 "competitive information spread with confirmation bias in cyber social networks"):
  Abstract: This paper studies competitive information spread with confirmation bias in the cyber-social networks that comprises individuals in social networks and competitive information sources in cyber layer. The competitive information spread is formulated as a zero-sum game between the competitive information sources, whose pure Nash equilibrium is demonstrated to exist. The derived Nash equilibrium depends on the innate opinions, social network topology and parameters of confirmation bias. Nash equilibriums in the scenarios of neutral and extremal group of innate opinions are also investigated. Numerical examples in the context of the well-known Krackhardt's advice network are provided to demonstrate the correctness of theory results.

Includes members:
  Member "spread of information with confirmation bias in cyber social networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on inference of network topology and confirmation bias in cyber social networks")
  Member "optimal investment strategies for competing camps in a social network a broad framework":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on inference of network topology and confirmation bias in cyber social networks")
  Member "structural balance and opinion separation in trust mistrust social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "visualizing structural balance in signed networks")
  Member "opinion dynamics in social networks with hostile camps consensus vs polarization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "percolation threshold for competitive influence in random networks")

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.SI(Social and Information Networks)