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: "information contagion an empirical study of the spread of news on digg and twitter social networks"
  Abstract: Social networks have emerged as a critical factor in information dissemination, search, marketing, expertise and influence discovery, and potentially an important tool for mobilizing people. Social media has made social networks ubiquitous, and also given researchers access to massive quantities of data for empirical analysis. These data sets offer a rich source of evidence for studying dynamics of individual and group behavior, the structure of networks and global patterns of the flow of information on them. However, in most previous studies, the structure of the underlying networks was not directly visible but had to be inferred from the flow of information from one individual to another. As a result, we do not yet understand dynamics of information spread on networks or how the structure of the network affects it. We address this gap by analyzing data from two popular social news sites. Specifically, we extract social networks of active users on Digg and Twitter, and track how interest in news stories spreads among them. We show that social networks play a crucial role in the spread of information on these sites, and that network structure affects dynamics of information flow.

Connected through hyperedge HE-1 (induced by source paper "modeling information diffusion in online social networks with partial differential equations"):
  with members:
    - "information diffusion and external influence in networks"
    - "diffusive logistic model towards predicting information diffusion in online social networks"
    - "on the interplay between social and topical structure"
    - "what stops social epidemics"
    - "a framework for quantitative analysis of cascades on networks"

Connected through hyperedge HE-2 (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"
    - "stability of spreading processes over time varying large scale networks"
    - "epidemic processes over adaptive state dependent networks"
    - "improved bounds on the epidemic threshold of exact sis models on complex networks"

Connected through hyperedge HE-3 (induced by source paper "temporal network representation learning"):
  with members:
    - "heterogeneous network motifs"
    - "node2bits compact time and attribute aware node representations for user stitching"
    - "dylink2vec effective feature representation for link prediction in dynamic networks"
    - "models for capturing temporal smoothness in evolving networks for learning latent representation of nodes"
    - "deep generative dual memory network for continual learning"
    - "attributed social network embedding"
    - "struc2vec learning node representations from structural identity"
    - "psdvec a toolbox for incremental and scalable word embedding"

Connected through hyperedge HE-4 (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-5 (induced by source paper "online reactions to the 2017 unite the right rally in charlottesville measuring polarization in twitter networks using media followership"):
  with members:
    - "social network analysis for social neuroscientists"
    - "its all in a name detecting and labeling bots by their name"
    - "centrality in modular networks"
    - "a quantitative approach to understanding online antisemitism"
    - "who let the trolls out towards understanding state sponsored trolls"
    - "on the origins of memes by means of fringe web communities"
    - "a long term analysis of polarization on twitter"
    - "botornot a system to evaluate social bots"

Connected through hyperedge HE-6 (induced by source paper "discovering patterns of online popularity from time series"):
  with members:
    - "expecting to be hip hawkes intensity processes for social media popularity"
    - "toeplitz inverse covariance based clustering of multivariate time series data"
    - "online human bot interactions detection estimation and characterization"
    - "botornot a system to evaluate social bots"
    - "on the dynamics of social media popularity a youtube case study"
    - "is the sample good enough comparing data from twitter s streaming api with twitter s firehose"
    - "dynamical classes of collective attention in twitter"
    - "novelty and collective attention"

Connected through hyperedge HE-7 (induced by source paper "toward maximizing the visibility of content in social media brand pages a temporal analysis"):
  with members:
    - "online popularity under promotion viral potential forecasting and the economics of time"
    - "multistage campaigning in social networks"
    - "when to post on social networks"
    - "klout score measuring influence across multiple social networks"
    - "dynamical classes of collective attention in twitter"
    - "trends in social media persistence and decay"
    - "predicting the popularity of online content"

Connected through hyperedge HE-8 (induced by source paper "beyond worst case in approximability of nonsubmodular influence maximization"):
  with members:
    - "don t be greedy leveraging community structure to find high quality seed sets for influence maximization"
    - "robust influence maximization"
    - "robust influence maximization"
    - "competitive contagion in 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.CY(Computers and Society)