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: "spread of information with confirmation bias in cyber social networks"
  Abstract: This paper provides a model to investigate information spreading over cyber-social network of agents communicating with each other. The cyber-social network considered here comprises individuals and news agencies. Each individual holds a belief represented by a scalar. Individuals receive information from news agencies that are closer to their belief, confirmation bias is explicitly incorporated into the model. The proposed dynamics of cyber-social networks is adopted from DeGroot-Friedkin model, where the individual's opinion update mechanism is a convex combination of his innate opinion, his neighbors' opinions at the previous time step (obtained from the social network), and the opinions passed along by news agencies from cyber layer which he follows. The characteristics of the interdependent social and cyber networks are radically different here: the social network relies on trust and hence static while the news agencies are highly dynamic since they are weighted as a function of the distance between an individual state and the state of news agency to account for confirmation bias. The conditions for convergence of the aforementioned dynamics to a unique equilibrium are characterized. The estimation and exact computation of the steady-state values under non-linear and linear state-dependent weight functions are provided. Finally, the impact of polarization in the opinions of news agencies on the public opinion evolution is numerically analyzed in the context of the well-known Krackhardt's advice network.

Connected through hyperedge HE-1 (induced by source paper "on inference of network topology and confirmation bias in cyber social networks"):
  with members:
    - "semi blind inference of topologies and dynamical processes over dynamic graphs"
    - "polarization and fake news early warning of potential misinformation targets"
    - "opinion dynamics with varying susceptibility to persuasion"
    - "fake news in social networks"
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "optimal investment strategies for competing camps in a social network a broad framework"
    - "network inference from consensus dynamics"
    - "characterization and inference of graph diffusion processes from observations of stationary signals"

Connected through hyperedge HE-2 (induced by source paper "competitive information spread with confirmation bias in cyber social networks"):
  with members:
    - "optimal investment strategies for competing camps in a social network a broad framework"
    - "structural balance and opinion separation in trust mistrust social networks"
    - "opinion dynamics in social networks with hostile camps consensus vs polarization"

Connected through hyperedge HE-3 (induced by source paper "a risk security tradeoff in graphical coordination games"):
  with members:
    - "security against impersonation attacks in distributed systems"
    - "distributed optimization under adversarial nodes"
    - "metastability of logit dynamics for coordination games"

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)