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: "stability of spreading processes over time varying large scale networks"
  Abstract: In this paper, we analyze the dynamics of spreading processes taking place over time-varying networks. A common approach to model time-varying networks is via Markovian random graph processes. This modeling approach presents the following limitation: Markovian random graphs can only replicate switching patterns with exponential inter-switching times, while in real applications these times are usually far from exponential. In this paper, we introduce a flexible and tractable extended family of processes able to replicate, with arbitrary accuracy, any distribution of inter-switching times. We then study the stability of spreading processes in this extended family. We first show that a direct analysis based on Ito's formula provides stability conditions in terms of the eigenvalues of a matrix whose size grows exponentially with the number of edges. To overcome this limitation, we derive alternative stability conditions involving the eigenvalues of a matrix whose size grows linearly with the number of nodes. Based on our results, we also show that heuristics based on aggregated static networks approximate the epidemic threshold more accurately as the number of nodes grows, or the temporal volatility of the random graph process is reduced. Finally, we illustrate our findings via numerical simulations.

Connected through hyperedge HE-1 (induced by source paper "stability of sis spreading processes in networks with non markovian transmission and recovery"):
  with members:
    - "second order moment closure for tighter epidemic thresholds"
    - "optimal containment of epidemics in temporal and adaptive networks"
    - "epidemic processes over adaptive state dependent networks"
    - "improved bounds on the epidemic threshold of exact sis models on complex networks"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"

Connected through hyperedge HE-2 (induced by source paper "efficient containment of exact sir markovian processes on networks"):
  with members:
    - "epidemic processes over adaptive state dependent networks"
    - "optimal patching in clustered malware epidemics"
    - "when is a network epidemic hard to eliminate"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"

Connected through hyperedge HE-3 (induced by source paper "contact adaption during epidemics a multilayer network formulation approach"):
  with members:
    - "epidemic processes over adaptive state dependent networks"
    - "disease spread over randomly switched large scale networks"
    - "a convex framework for optimal investment on disease awareness in social networks"

Connected through hyperedge HE-4 (induced by source paper "resource allocation for containing epidemics from temporal network data"):
  with members:
    - "epidemic processes over adaptive state dependent networks"
    - "decentralized protection strategies against sis epidemics in networks"

Connected through hyperedge HE-5 (induced by source paper "optimal containment of epidemics in temporal and adaptive networks"):
  with members:
    - "efficient containment of exact sir markovian processes on networks"
    - "epidemic processes over adaptive state dependent networks"
    - "decentralized protection strategies against sis epidemics in networks"
    - "co evolutionary dynamics in social networks a case study of twitter"
    - "an efficient curing policy for epidemics on graphs"
    - "a convex framework for optimal investment on disease awareness in social networks"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"
    - "spectral analysis of virus spreading in random geometric networks"

Connected through hyperedge HE-6 (induced by source paper "random graph models for dynamic networks"):
  with members:
    - "clustering network layers with the strata multilayer stochastic block model"
    - "stochastic block transition models for dynamic networks"
    - "nonparametric multi group membership model for dynamic networks"
    - "dynamic stochastic blockmodels statistical models for time evolving networks"
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"

Connected through hyperedge HE-7 (induced by source paper "on the dynamics of deterministic epidemic propagation over networks"):
  with members:
    - "second order moment closure for tighter epidemic thresholds"
    - "sirs epidemics on complex networks concurrence of exact markov chain and approximated models"
    - "competitive contagion in networks"

Connected through hyperedge HE-8 (induced by source paper "the damage inflicted by a computer virus a new estimation method"):
  with members:
    - "optimal patching in clustered malware epidemics"

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)