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: "majority model on random regular graphs"
  Abstract: Consider a graph $G=(V,E)$ and an initial random coloring where each vertex $v \in V$ is blue with probability $P_b$ and red otherwise, independently from all other vertices. In each round, all vertices simultaneously switch their color to the most frequent color in their neighborhood and in case of a tie, a vertex keeps its current color. The main goal of the present paper is to analyze the behavior of this basic and natural process on the random $d$-regular graph $\mathbb{G}_{n,d}$. It is shown that for all $\epsilon>0$, $P_b \le 1/2-\epsilon$ results in final complete occupancy by red in $\mathcal{O}(\log_d\log n)$ rounds with high probability, provided that $d\geq c/\epsilon^2$ for a suitable constant $c$. Furthermore, we show that with high probability, $\mathbb{G}_{n,d}$ is immune; i.e., the smallest dynamic monopoly is of linear size. A dynamic monopoly is a subset of vertices that can take over in the sense that a commonly chosen initial color eventually spreads throughout the whole graph, irrespective of the colors of other vertices. This answers an open question of Peleg.

Connected through hyperedge HE-1 (induced by source paper "influencing opinion dynamics in networks with limited interaction"):
  with members:
    - "influencing opinions of heterogeneous populations over finite time horizons"
    - "incentivized campaigning in social networks"
    - "how to run a campaign optimal control of sis and sir information epidemics"

Connected through hyperedge HE-2 (induced by source paper "stabilization time in minority processes"):
  with members:
    - "stabilization time in weighted minority processes"
    - "on the voting time of the deterministic majority process"
    - "anti coordination games and stable graph colorings"
    - "progresses in the analysis of stochastic 2d cellular automata a study of asynchronous 2d minority"

Connected through hyperedge HE-3 (induced by source paper "robustness and efficiency of leaderless probabilistic consensus protocols within byzantine infrastructures"):
  with members:
    - "global majority consensus by local majority polling on graphs of a given degree sequence"
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "fast deterministic consensus in a noisy environment"

Connected through hyperedge HE-4 (induced by source paper "fake news and rumors a trigger for proliferation or fading away"):
  with members:
    - "phase transition in democratic opinion dynamics"
    - "opinion forming in erdos renyi random graph and expanders"

Connected through hyperedge HE-5 (induced by source paper "target set in threshold models"):
  with members:
    - "opinion forming in erdos renyi random graph and expanders"
    - "tight bounds on the minimum size of a dynamic monopoly"

Connected through hyperedge HE-6 (induced by source paper "tight bounds on the minimum size of a dynamic monopoly"):
  with members:
    - "dynamic monopolies in reversible bootstrap percolation"
    - "opinion forming in erdos renyi random graph and expanders"
    - "biased majority rule cellular automata"
    - "contagious sets in dense graphs"
    - "contagious sets in expanders"

Connected through hyperedge HE-7 (induced by source paper "opinion forming in binomial random graph and expanders"):
  with members:
    - "dynamic monopolies in reversible bootstrap percolation"
    - "biased majority rule cellular automata"

Connected through hyperedge HE-8 (induced by source paper "dynamic monopolies in reversible bootstrap percolation"):
  with members:
    - "biased majority rule cellular automata"

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.DS(Data Structures and Algorithms)