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: "opinion dynamics in social networks with hostile camps consensus vs polarization"
  Abstract: Most of the distributed protocols for multi-agent consensus assume that the agents are mutually cooperative and “trustful,” and so the couplings among the agents bring the values of their states closer. Opinion dynamics in social groups, however, require beyond these conventional models due to ubiquitous competition and distrust between some pairs of agents, which are usually characterized by repulsive couplings and may lead to clustering of the opinions. A simple yet insightful model of opinion dynamics with both attractive and repulsive couplings was proposed recently by C. Altafini, who examined first-order consensus algorithms over static signed graphs. This protocol establishes modulus consensus, where the opinions become the same in modulus but may differ in signs. In this paper, we extend the modulus consensus model to the case where the network topology is an arbitrary time-varying signed graph and prove reaching modulus consensus under mild sufficient conditions of uniform connectivity of the graph. For cut-balanced graphs, not only sufficient, but also necessary conditions for modulus consensus are given.

Connected through hyperedge HE-1 (induced by source paper "percolation threshold for competitive influence in random networks"):
  with members:
    - "on misinformation containment in online social networks"
    - "a two phase investment game for competitive opinion dynamics in social networks"
    - "distributed rumor blocking with multiple positive cascades"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-2 (induced by source paper "perceptual control with large feature and actuator networks"):
  with members:
    - "novel multidimensional models of opinion dynamics in social networks"
    - "optical flow sensing and the inverse perception problem for flying bats"
    - "control communication complexity of distributed actions"
    - "animal inspired agile flight using optical flow sensing"

Connected through hyperedge HE-3 (induced by source paper "competitive information spread with confirmation bias in cyber social networks"):
  with members:
    - "spread of information with confirmation bias in cyber social networks"
    - "optimal investment strategies for competing camps in a social network a broad framework"
    - "structural balance and opinion separation in trust mistrust social networks"

Connected through hyperedge HE-4 (induced by source paper "a two phase investment game for competitive opinion dynamics in social networks"):
  with members:
    - "an integrated framework for competitive multi channel marketing of multi featured products"
    - "multi round influence maximization"
    - "effectiveness of diffusing information through a social network in multiple phases"
    - "optimal multiphase investment strategies for influencing opinions in a social network"
    - "adaptive influence maximization in dynamic social networks"
    - "optimal investment strategies for competing camps in a social network a broad framework"
    - "information diffusion in social networks in two phases"
    - "no time to observe adaptive influence maximization with partial feedback"

Connected through hyperedge HE-5 (induced by source paper "structured networks and coarse grained descriptions a dynamical perspective"):
  with members:
    - "multiscale dynamical embeddings of complex networks"
    - "a tutorial on modeling and analysis of dynamic social networks part i"
    - "the many facets of community detection in complex networks"
    - "the ground truth about metadata and community detection in networks"
    - "seismic a self exciting point process model for predicting tweet popularity"
    - "spectra of random graphs with community structure and arbitrary degrees"
    - "spectral redemption in clustering sparse networks"
    - "opinion fluctuations and disagreement in social networks"

Connected through hyperedge HE-6 (induced by source paper "cooperative opinion dynamics on multiple interdependent topics modeling and analysis"):
  with members:
    - "continuous time opinion dynamics on multiple interdependent topics"
    - "cooperative opinion dynamics on multiple interdependent topics modeling and some observations"
    - "novel multidimensional models of opinion dynamics in social networks"
    - "evolution of social power in social networks with dynamic topology"
    - "the impact of random actions on opinion dynamics"
    - "game theoretic analysis of the hegselmann krause model for opinion dynamics in finite dimensions"

Connected through hyperedge HE-7 (induced by source paper "an influence network model to study discrepancies in expressed and private opinions"):
  with members:
    - "a tutorial on modeling and analysis of dynamic social networks part i"
    - "evolution of social power in social networks with dynamic topology"
    - "a psychologically motivated model of opinion change with applications to american politics"
    - "biased assimilation homophily and the dynamics of polarization"

Connected through hyperedge HE-8 (induced by source paper "continuous time opinion dynamics on multiple interdependent topics"):
  with members:
    - "consensus and disagreement of heterogeneous belief systems in influence networks"
    - "a tutorial on modeling and analysis of dynamic social networks part i"
    - "novel multidimensional models of opinion dynamics in social 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.SY(Systems and Control)