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 "differential inequalities in multi agent coordination and opinion dynamics modeling"):
  Abstract: Abstract   Many distributed algorithms for multi-agent coordination employ the simple averaging dynamics, referred to as the  Laplacian flow . Besides the standard consensus protocols, examples include, but are not limited to, algorithms for aggregation and containment control, target surrounding, distributed optimization and models of opinion formation in social groups. In spite of their similarities, each of these algorithms has been studied using separate mathematical techniques. In this paper, we show that stability and convergence of many coordination algorithms involving the Laplacian flow dynamics follow from the general  consensus dichotomy  property of a special differential inequality. The consensus dichotomy implies that any solution to the differential inequality is either unbounded or converges to a consensus equilibrium. In this paper, we establish the dichotomy criteria for differential inequalities and illustrate their applications to multi-agent coordination and opinion dynamics modeling.

Includes members:
  Member "a tutorial on modeling and analysis of dynamic social networks part i":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ideotrace a framework for ideology tracing with a case study on the 2016 u s presidential election")
  Member "structural balance and opinion separation in trust mistrust social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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-3 (induced by source paper "percolation threshold for competitive influence in random networks")
  Member "distributed surrounding design of target region with complex adjacency matrices":
    also connected through other hyperedges:
      (none)
  Member "biased assimilation homophily and the dynamics of polarization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "reaching an optimal consensus dynamical systems that compute intersections of convex sets":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a tutorial on modeling and analysis of dynamic social networks part i")
  Member "convergence of type symmetric and cut balanced consensus seeking systems extended version":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "persistent flows and non reciprocal interactions in deterministic networks")
  Member "the role of persistent graphs in the agreement seeking of social networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a tutorial on modeling and analysis of dynamic social networks part i")

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.SY(Systems and Control)