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: "a convex framework for optimal investment on disease awareness in social networks"
  Abstract: We consider the problem of controlling the propagation of an epidemic outbreak in an arbitrary network of contacts by investing on disease awareness throughout the network. We model the effect of agent awareness on the dynamics of an epidemic using the SAIS epidemic model, an extension of the SIS epidemic model that includes a state of “awareness”. This model allows to derive a condition to control the spread of an epidemic outbreak in terms of the eigenvalues of a matrix that depends on the network structure and the parameters of the model. We study the problem of finding the cost-optimal investment on disease awareness throughout the network when the cost function presents some realistic properties. We propose a convex framework to find cost-optimal allocation of resources. We validate our results with numerical simulations in a real online social network.

Connected through hyperedge HE-1 (induced by source paper "contact adaption during epidemics a multilayer network formulation approach"):
  with members:
    - "stability of spreading processes over time varying large scale networks"
    - "epidemic processes over adaptive state dependent networks"
    - "disease spread over randomly switched large scale networks"

Connected through hyperedge HE-2 (induced by source paper "optimal containment of epidemics in temporal and adaptive networks"):
  with members:
    - "efficient containment of exact sir markovian processes on networks"
    - "stability of spreading processes over time varying large scale 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"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"
    - "spectral analysis of virus spreading in random geometric networks"

Connected through hyperedge HE-3 (induced by source paper "bio inspired framework for allocation of protection resources in cyber physical networks"):
  with members:
    - "stability of spreading processes over time varying large scale networks"
    - "epidemic processes over adaptive state dependent networks"
    - "worst case scenarios for greedy centrality based network protection strategies"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"
    - "spectral analysis of virus spreading in random geometric networks"

Connected through hyperedge HE-4 (induced by source paper "spreading processes over socio technical networks with phase type transmissions"):
  with members:
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"

Connected through hyperedge HE-5 (induced by source paper "disease spread over randomly switched large scale networks"):
  with members:
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"

Connected through hyperedge HE-6 (induced by source paper "cost optimal switching protection strategy in adaptive networks"):
  with members:
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"

Connected through hyperedge HE-7 (induced by source paper "traffic control for network protection against spreading processes"):
  with members:
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"

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)