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: "pseudo cores the terminus of an intelligent viral meme s trajectory"
  Abstract: Comprehending the virality of a meme can help us in addressing the problems pertaining to disciplines like epidemiology and digital marketing. Therefore, it is not surprising that memetics remains a highly analyzed research topic ever since the mid 1990s. Some scientists choose to investigate the intrinsic contagiousness of a meme while others study the problem from a network theory perspective. In this paper, we revisit the idea of a core-periphery structure and apply it to understand the trajectory of a viral meme in a social network. We have proposed shell-based hill climbing algorithms to determine the path from a periphery shell(where the meme originates) to the core of the network. Further simulations and analysis on the networks behavioral characteristics helped us unearth specialized shells which we term Pseudo-Cores. These shells emulate the behavior of the core in terms of size of the cascade triggered. In our experiments, we have considered two sets for the target nodes, one being core and the other being any of the pseudo-core. We compare our algorithms against already existing path finding algorithms and validate the better performance experimentally.

Connected through hyperedge HE-1 (induced by source paper "estimating shell index in a graph with local information"):
  with members:
    - "global rank estimation"
    - "a faster method to estimate closeness centrality ranking"
    - "degree ranking using local information"
    - "modeling memetics using edge diversity"
    - "rank me thou shalln t compare me"
    - "evolving models for meso scale structures"
    - "understanding spreading patterns on social networks based on network topology"
    - "estimating the degree centrality ranking of a node"

Connected through hyperedge HE-2 (induced by source paper "evolving models for meso scale structures"):
  with members:
    - "understanding spreading patterns on social networks based on network topology"

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)