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: "using friends as sensors to detect global scale contagious outbreaks"
  Abstract: Recent research has focused on the monitoring of global-scale online data for improved detection of epidemics, mood patterns, movements in the stock market, political revolutions, box-office revenues, consumer behaviour and many other important phenomena. However, privacy considerations and the sheer scale of data available online are quickly making global monitoring infeasible, and existing methods do not take full advantage of local network structure to identify key nodes for monitoring. Here, we develop a model of the contagious spread of information in a global-scale, publicly-articulated social network and show that a simple method can yield not just early detection, but advance warning of contagious outbreaks. In this method, we randomly choose a small fraction of nodes in the network and then we randomly choose a "friend" of each node to include in a group for local monitoring. Using six months of data from most of the full Twittersphere, we show that this friend group is more central in the network and it helps us to detect viral outbreaks of the use of novel hashtags about 7 days earlier than we could with an equal-sized randomly chosen group. Moreover, the method actually works better than expected due to network structure alone because highly central actors are both more active and exhibit increased diversity in the information they transmit to others. These results suggest that local monitoring is not just more efficient, it is more effective, and it is possible that other contagious processes in global-scale networks may be similarly monitored.

Connected through hyperedge HE-1 (induced by source paper "information diffusion in social networks friendship paradox based models and statistical inference"):
  with members:
    - "what do your friends think efficient polling methods for networks using friendship paradox"
    - "centrality friendship paradoxes when our friends are more important than us"
    - "conjoining uncooperative societies facilitates evolution of cooperation"
    - "contagions in social networks effects of monophilic contagion friendship paradox and reactive networks"
    - "which friends are more popular than you contact strength and the friendship paradox in social networks"
    - "influence maximization over markovian graphs a stochastic optimization approach"
    - "engagement dynamics and sensitivity analysis of youtube videos"
    - "the majority illusion in social networks"

Connected through hyperedge HE-2 (induced by source paper "maximum likelihood estimation of power law degree distributions using friendship paradox based sampling"):
  with members:
    - "information diffusion in social networks friendship paradox based models and statistical inference"
    - "centrality friendship paradoxes when our friends are more important than us"
    - "which friends are more popular than you contact strength and the friendship paradox in social networks"
    - "the majority illusion in social networks"
    - "qualities and inequalities in online social networks through the lens of the generalized friendship paradox"
    - "tracking infection diffusion in social networks filtering algorithms and threshold bounds"
    - "network weirdness exploring the origins of network paradoxes"
    - "friendship paradox redux your friends are more interesting than you"

Connected through hyperedge HE-3 (induced by source paper "what do your friends think efficient polling methods for networks using friendship paradox"):
  with members:
    - "information diffusion in social networks friendship paradox based models and statistical inference"
    - "friendship paradox biases perceptions in directed networks"
    - "centrality friendship paradoxes when our friends are more important than us"
    - "gemsec graph embedding with self clustering"
    - "the majority illusion in social networks"
    - "qualities and inequalities in online social networks through the lens of the generalized friendship paradox"
    - "online reputation and polling systems data incest social learning and revealed preferences"
    - "generalized friendship paradox in complex networks the case of scientific collaboration"

Connected through hyperedge HE-4 (induced by source paper "contagions in social networks effects of monophilic contagion friendship paradox and reactive networks"):
  with members:
    - "what do your friends think efficient polling methods for networks using friendship paradox"
    - "centrality friendship paradoxes when our friends are more important than us"
    - "which friends are more popular than you contact strength and the friendship paradox in social networks"
    - "influence maximization over markovian graphs a stochastic optimization approach"
    - "the happiness paradox your friends are happier than you"
    - "tracking infection diffusion in social networks filtering algorithms and threshold bounds"
    - "scalable methods for adaptively seeding a social network"
    - "friendship paradox redux your friends are more interesting than you"

Connected through hyperedge HE-5 (induced by source paper "centrality friendship paradoxes when our friends are more important than us"):
  with members:
    - "the happiness paradox your friends are happier than you"
    - "network weirdness exploring the origins of network paradoxes"
    - "generalized friendship paradox in complex networks the case of scientific collaboration"
    - "friendship paradox redux your friends are more interesting than you"
    - "total communicability as a centrality measure"

Connected through hyperedge HE-6 (induced by source paper "effectiveness of alter sampling in social networks"):
  with members:
    - "defining and evaluating network communities based on ground truth"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "community structure in large networks natural cluster sizes and the absence of large well defined clusters"

Connected through hyperedge HE-7 (induced by source paper "optimizing node discovery on networks problem definitions fast algorithms and observations"):
  with members:
    - "optimal tagging with markov chain optimization"
    - "powerwalk scalable personalized pagerank via random walks with vertex centric decomposition"
    - "scalable betweenness centrality maximization via sampling"
    - "absorbing random walk centrality theory and algorithms"
    - "computing classic closeness centrality at scale"
    - "axioms for centrality"
    - "random walk domination in large graphs problem definitions and fast solutions"
    - "a tractable approach to finding closest truncated commute time neighbors in large graphs"

Connected through hyperedge HE-8 (induced by source paper "which friends are more popular than you contact strength and the friendship paradox in social networks"):
  with members:
    - "collective attention in the age of mis information"
    - "generalized friendship paradox in complex networks the case of scientific collaboration"
    - "friendship paradox redux your friends are more interesting than you"
    - "the anatomy of the facebook social graph"

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)