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 is not a virus and other consequences of human cognitive limits"
  Abstract: The many decisions people make about what to pay attention to online shape the spread of information in online social networks. Due to the constraints of available time and cognitive resources, the ease of discovery strongly impacts how people allocate their attention to social media content. As a consequence, the position of information in an individual's social feed, as well as explicit social signals about its popularity, determine whether it will be seen, and the likelihood that it will be shared with followers. Accounting for these cognitive limits simplifies mechanics of information diffusion in online social networks and explains puzzling empirical observations: (i) information generally fails to spread in social media and (ii) highly connected people are less likely to re-share information. Studies of information diffusion on different social media platforms reviewed here suggest that the interplay between human cognitive limits and network structure differentiates the spread of information from other social contagions, such as the spread of a virus through a population.

Connected through hyperedge HE-1 (induced by source paper "the opacity problem in social contagion"):
  with members:
    - "node2vec scalable feature learning for networks"
    - "can cascades be predicted"
    - "geotagging one hundred million twitter accounts with total variation minimization"
    - "distributed representations of words and phrases and their compositionality"
    - "virality prediction and community structure in social networks"
    - "social influence in social advertising evidence from field experiments"
    - "what stops social epidemics"

Connected through hyperedge HE-2 (induced by source paper "models of continuous time networks with tie decay diffusion and convection"):
  with members:
    - "tempus volat hora fugit a survey of dynamic network models in discrete and continuous time"
    - "social contagion an empirical study of information spread on digg and twitter follower graphs"

Connected through hyperedge HE-3 (induced by source paper "can you trust the trend discovering simpson s paradoxes in social data"):
  with members:
    - "on quitting performance and practice in online game play"
    - "evidence of online performance deterioration in user sessions on reddit"
    - "averaging gone wrong using time aware analyses to better understand behavior"
    - "the simple rules of social contagion"
    - "what stops social epidemics"

Connected through hyperedge HE-4 (induced by source paper "computational social scientist beware simpson s paradox in behavioral data"):
  with members:
    - "can you trust the trend discovering simpson s paradoxes in social data"
    - "dynamics of content quality in collaborative knowledge production"
    - "evidence of online performance deterioration in user sessions on reddit"
    - "averaging gone wrong using time aware analyses to better understand behavior"
    - "the simple rules of social contagion"
    - "portrait of an online shopper understanding and predicting consumer behavior"
    - "social dynamics of digg"
    - "what stops social epidemics"

Connected through hyperedge HE-5 (induced by source paper "a new method to reduce overestimation of thresholds with observational network data"):
  with members:
    - "geotagging one hundred million twitter accounts with total variation minimization"
    - "distributed representations of words and phrases and their compositionality"
    - "virality prediction and community structure in social networks"
    - "what stops social epidemics"

Connected through hyperedge HE-6 (induced by source paper "latent viral marketing concepts and control methods"):
  with members:
    - "sequential seeding in complex networks trading speed for coverage"
    - "a scalable heuristic for viral marketing under the tipping model"
    - "the role of social networks in information diffusion"

Connected through hyperedge HE-7 (induced by source paper "bounded rationality in scholarly knowledge discovery"):
  with members:
    - "the simple rules of social contagion"
    - "dynamical classes of collective attention in twitter"

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)