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: "technological networks and the spread of computer viruses"
  Abstract: Computer infections such as viruses and worms spread over networks of contacts between computers, with different types of networks being exploited by different types of infections. Here we analyze the structures of several of these networks, exploring their implications for modes of spread and the control of infection. We argue that vaccination strategies that focus on a limited number of network nodes, whether targeted or randomly chosen, are in many cases unlikely to be effective. An alternative dynamic mechanism for the control of contagion, called throttling, is introduced and argued to be effective under a range of conditions.

Connected through hyperedge HE-1 (induced by source paper "new phenomena in large scale internet traffic"):
  with members:
    - "ell_0 motivated low rank sparse subspace clustering"
    - "interactive supercomputing on 40 000 cores for machine learning and data analysis"
    - "hyperscaling internet graph analysis with d4m on the mit supercloud"
    - "scaling in internet traffic a 14 year and 3 day longitudinal study with multiscale analyses and random projections"
    - "control principles of complex networks"

Connected through hyperedge HE-2 (induced by source paper "hypersparse neural network analysis of large scale internet traffic"):
  with members:
    - "ell_0 motivated low rank sparse subspace clustering"
    - "interactive supercomputing on 40 000 cores for machine learning and data analysis"
    - "hyperscaling internet graph analysis with d4m on the mit supercloud"
    - "scaling in internet traffic a 14 year and 3 day longitudinal study with multiscale analyses and random projections"

Connected through hyperedge HE-3 (induced by source paper "joint inference of user community and interest patterns in social interaction networks"):
  with members:
    - "crisis communication patterns in social media during hurricane sandy"
    - "performance of social network sensors during hurricane sandy"
    - "virality prediction and community structure in social networks"
    - "the author topic model for authors and documents"

Connected through hyperedge HE-4 (induced by source paper "understanding information spreading in social media during hurricane sandy user activity and network properties"):
  with members:
    - "performance of social network sensors during hurricane sandy"
    - "virality prediction and community structure in social networks"
    - "time critical social mobilization"

Connected through hyperedge HE-5 (induced by source paper "analyzing social interaction networks from twitter for planned special events"):
  with members:
    - "time critical social mobilization"

Connected through hyperedge HE-6 (induced by source paper "generic anomalous vertices detection utilizing a link prediction algorithm"):
  with members:
    - "analyzing complex network user arrival patterns and their effect on network topologies"
    - "graph based anomaly detection and description a survey"

Connected through hyperedge HE-7 (induced by source paper "context dependent preferential attachment model for complex networks"):
  with members:
    - "degree relations of triangles in real world networks and graph models"

Connected through hyperedge HE-8 (induced by source paper "beyond the blacklist modeling malware spread and the effect of interventions"):
  with members:
    - "modeling internet scale policies for cleaning up malware"
    - "on the universality of rank distributions of website popularity"

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.NI(Networking and Internet Architecture)