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: "randomized rumor spreading in poorly connected small world networks"
  Abstract: Push-Pull is a well-studied round-robin rumor spreading protocol defined as follows: initially a node knows a rumor and wants to spread it to all nodes in a network quickly. In each round, every informed node sends the rumor to a random neighbor, and every uninformed node contacts a random neighbor and gets the rumor from her if she knows it. We analyze this protocol on random $k$-trees, a class of power law graphs, which are small-world and have large clustering coefficients, built as follows: initially we have a $k$-clique. In every step a new node is born, a random $k$-clique of the current graph is chosen, and the new node is joined to all nodes of the $k$-clique. When $k>1$ is fixed, we show that if initially a random node is aware of the rumor, then with probability $1-o(1)$ after $O\left((\log n)^{1+2/k}\cdot\log\log n\cdot f(n)\right)$ rounds the rumor propagates to $n-o(n)$ nodes, where $n$ is the number of nodes and $f(n)$ is any slowly growing function. Since these graphs have polynomially small conductance, vertex expansion $O(1/n)$ and constant treewidth, these results demonstrate that Push-Pull can be efficient even on poorly connected networks. On the negative side, we prove that with probability $1-o(1)$ the protocol needs at least $\Omega\left(n^{(k-1)/(k^2+k-1)}/f^2(n)\right)$ rounds to inform all nodes. This exponential dichotomy between time required for informing almost all and all nodes is striking. Our main contribution is to present, for the first time, a natural class of random graphs in which such a phenomenon can be observed. Our technique for proving the upper bound carries over to a closely related class of graphs, random $k$-Apollonian networks, for which we prove an upper bound of $O\left((\log n)^{c_k}\cdot\log\log n\cdot f(n)\right)$ rounds for informing $n-o(n)$ nodes with probability $1-o(1)$ when $k>2$ is fixed. Here, $c_k=(k^2-3)/(k-1)^2<1 + 2/k$.

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)