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: "stochastic models of user contributory web sites"
  Abstract: We describe a general stochastic processes-based approach to modeling user-contributory web sites, where users create, rate and share content. These models describe aggregate measures of activity and how they arise from simple models of individual users. This approach provides a tractable method to understand user activity on the web site and how this activity depends on web site design choices, especially the choice of what information about other users' behaviors is shown to each user. We illustrate this modeling approach in the context of user-created content on the news rating site Digg.

Connected through hyperedge HE-1 (induced by source paper "modeling the popularity of twitter hashtags with master equations"):
  with members:
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "validation of twitter opinion trends with national polling aggregates hillary clinton vs donald trump"
    - "modeling the infectiousness of twitter hashtags"
    - "virality prediction and community structure in social networks"
    - "the pulse of news in social media forecasting popularity"
    - "novelty and collective attention"

Connected through hyperedge HE-2 (induced by source paper "sequential voting promotes collective discovery in social recommendation systems"):
  with members:
    - "can cascades be predicted"
    - "predicting the popularity of online content"

Connected through hyperedge HE-3 (induced by source paper "an agent based model of message propagation in the facebook electronic social network"):
  with members:
    - "four degrees of separation"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"

Connected through hyperedge HE-4 (induced by source paper "online social network analysis a survey of research applications in computer science"):
  with members:
    - "inheritance patterns in citation networks reveal scientific memes"
    - "who will retweet this automatically identifying and engaging strangers on twitter to spread information"
    - "networkit an interactive tool suite for high performance network analysis"
    - "networkit a tool suite for large scale complex network analysis"
    - "can cascades be predicted"
    - "exploring image virality in google plus"
    - "popularity prediction in microblogging network a case study on sina weibo"
    - "a scalable heuristic for viral marketing under the tipping model"

Connected through hyperedge HE-5 (induced by source paper "popularity and quality in social news aggregators a study of reddit and hacker news"):
  with members:
    - "can cascades be predicted"
    - "measuring and optimizing cultural markets"
    - "the pulse of news in social media forecasting popularity"
    - "the role of social networks in information diffusion"
    - "using a model of social dynamics to predict popularity of news"

Connected through hyperedge HE-6 (induced by source paper "stochastic models predict user behavior in social media"):
  with members:
    - "friendship paradox redux your friends are more interesting than you"
    - "collaborative topic regression with social matrix factorization for recommendation systems"
    - "social dynamics of digg"
    - "using stochastic models to describe and predict social dynamics of web users"
    - "predicting the popularity of online content"
    - "analysis of social voting patterns on digg"
    - "social information processing in news aggregation"

Connected through hyperedge HE-7 (induced by source paper "social contagion an empirical study of information spread on digg and twitter follower graphs"):
  with members:
    - "social dynamics of digg"
    - "what stops social epidemics"
    - "entropy based classification of retweeting activity on twitter"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "using a model of social dynamics to predict popularity of news"
    - "a framework for quantitative analysis of cascades on networks"
    - "predicting influential users in online social networks"
    - "analysis of social voting patterns on digg"

Connected through hyperedge HE-8 (induced by source paper "rethinking centrality the role of dynamical processes in social network analysis"):
  with members:
    - "the simple rules of social contagion"
    - "social dynamics of digg"
    - "what stops social epidemics"
    - "entropy based classification of retweeting activity on twitter"
    - "parameterized centrality metric for network analysis"
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "a framework for quantitative analysis of cascades on networks"
    - "influence and passivity in social media"

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)