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: "toward understanding friendship in online social networks"
  Abstract: All major on-line social networks, such as MySpace, Facebook, LiveJournal, and Orkut, are built around the concept of friendship. It is not uncommon for a social network participant to have over 100 friends. A natural question arises: are they all real friends of hers, or does she mean something different when she calls them "friends?" Speaking in other words, what is the relationship between off-line (real, traditional) friendship and its on-line (virtual) namesake? In this paper, we use sociological data to suggest that there is a significant difference between the concepts of virtual and real friendships. We further investigate the structure of on-line friendship and observe that it follows the Pareto (or double Pareto) distribution and is subject to age stratification but not to gender segregation. We introduce the concept of digital personality that quantifies the willingness of a social network participant to engage in virtual friendships.

Connected through hyperedge HE-1 (induced by source paper "a large scale community structure analysis in facebook"):
  with members:
    - "web data extraction applications and techniques"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "a novel measure of edge centrality in social networks"
    - "defining and evaluating network communities based on ground truth"
    - "partisan asymmetries in online political activity"
    - "a classification for community discovery methods in complex networks"
    - "generalized louvain method for community detection in large networks"
    - "the anatomy of the facebook social graph"

Connected through hyperedge HE-2 (induced by source paper "community structure in large networks natural cluster sizes and the absence of large well defined clusters"):
  with members:
    - "empirical comparison of algorithms for network community detection"
    - "topology and geometry of online social networks"
    - "a tutorial on spectral clustering"
    - "nearly linear time algorithms for graph partitioning graph sparsification and solving linear systems"
    - "mapping the gnutella network properties of large scale peer to peer systems and implications for system design"

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)