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: "bounding transport complexity for content dissemination in online social networks"
  Abstract: In this paper, we address the issue on measuring the transport difficulty for content dissemination in online social networks (OSNs). We define a new metric, called \emph{transport load}, to measure the load imposed by the OSN on the carrier communication network. It involves two key factors: data arrival process at users and transport distance of messages. Furthermore, we define the fundamental limit of transport load as the \emph{transport complexity}, i.e., the \emph{minimum required} transport load for an OSN over a given carrier communication network. To model the content dissemination in OSNs, we formulate the geographical distribution feature of dissemination sessions in OSNs by introducing a four-layered system model. It consists of physical layer, social layer, content layer, and session layer. We dig the mutual relevances among these four layers as the preconditions for bounding the transport complexity. Specifically, taking into account the scale-free property of users' degree centrality in OSNs, we introduce the Zipf's distribution to describe the friendship degree of users. Furthermore, in order to model the interest-driven session patterns in real-world OSNs, we define a new session pattern, called Social-InterestCast. Combining with the users' behaviour in real-life OSNs and the experimental results of our evaluation, we make a reasonable assumption that: For the session with a source node, say $v$, the number of destinations chosen from all friends of $v$ follows a Zipf's distribution. Based on our system model, we derive the lower bound on transport complexity for the content dissemination in a large-scale OSN under this common probability distribution in the social sciences.

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)