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 "improved intolerance intervals and size bounds for a schelling type spin system"):
  Abstract: We consider a Schelling model of self-organized segregation in an open system that is equivalent to a zero-temperature Ising model with Glauber dynamics, or an Asynchronous Cellular Automaton (ACA) with extended Moore neighborhoods. Previous work has shown that if the intolerance parameter of the model $\tau\in (\sim 0.488,\sim 0.512) \setminus \{1/2\}$, then for a sufficiently large neighborhood of interaction $N$, any particle will end up in an exponentially large monochromatic region almost surely. #R##N#This paper extends the above result to the interval $\tau \in (\sim 0.433,\sim 0.567) \setminus \{1/2\}$. We also improve the bounds on the size of the monochromatic region by exponential factors in $N$. Finally, we show that when particles are placed on the infinite lattice $\mathbb{Z}^2$ rather than on a flat torus, for the values of $\tau$ mentioned above, sufficiently large $N$, and after a sufficiently long evolution time, any particle is contained in a large monochromatic region of size exponential in $N$, almost surely. The new proof, critically relies on a novel geometric construction related to the formation of the monochromatic region.

Includes members:
  Member "self organized segregation on the grid":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a local stochastic algorithm for separation in heterogeneous self organizing particle systems")
  Member "minority population in the one dimensional schelling model of segregation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "self organized segregation on the grid")
  Member "unperturbed schelling segregation in two or three dimensions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "positive algorithmic bias cannot stop fragmentation in homophilic social networks")
  Member "digital morphogenesis via schelling segregation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "positive algorithmic bias cannot stop fragmentation in homophilic social networks")
  Member "an analysis of one dimensional schelling segregation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "positive algorithmic bias cannot stop fragmentation in homophilic social 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)