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: "wisdom of the crowd or wisdom of a few an analysis of users content generation"
  Abstract: In this paper we analyze how user generated content (UGC) is created, challenging the well known it wisdom of crowds concept. Although it is known that user activity in most settings follow a power law, that is, few people do a lot, while most do nothing, there are few studies that characterize well this activity. In our analysis of datasets from two different social networks, Facebook and Twitter, we find that a small percentage of active users and much less of all users represent 50% of the UGC. We also analyze the dynamic behavior of the generation of this content to find that the set of most active users is quite stable in time. Moreover, we study the social graph, finding that those active users area a highly connected among them. This implies that most of the wisdom comes from a few users challenging the independence assumption needed to have a wisdom of crowds. We also address the content that is never seen by any people (the digital desert), which challenges the assumption that the content of every person should be taken in account in the collective decision. At the end this is not surprising, as the Web is a reflection of our own society, where economical or political power also is in the hands of minorities

Connected through hyperedge HE-1 (induced by source paper "the size conundrum why online knowledge markets can fail at scale"):
  with members:
    - "community aliveness discovering interaction decay patterns in online social communities"
    - "uncovering the dynamics of crowdlearning and the value of knowledge"
    - "dynamics of content quality in collaborative knowledge production"
    - "activity dynamics in collaboration networks"
    - "social resilience in online communities the autopsy of friendster"

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)