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: "distance is not dead social interaction and geographical distance in the internet era"
  Abstract: The Internet revolution has made long-distance communication dramatically faster, easier, and cheaper than ever before. This, it has been argued, has decreased the importance of geographic proximity in social interactions, transforming our world into a global village with a borderless society. We argue for the opposite: while technology has undoubtedly increased the overall level of communication, this increase has been most pronounced for local social ties. We show that the volume of electronic communications is inversely proportional to geographic distance, following a Power Law. We directly study the importance of physical proximity in social interactions by analyzing the spatial dissemination of new baby names. Counter-intuitively, and in line with the above argument, the importance of geographic proximity has dramatically increased with the internet revolution.

Connected through hyperedge HE-1 (induced by source paper "competition between homophily and information entropy maximization in social networks"):
  with members:
    - "cumulative effect in information diffusion empirical study on a microblogging network"
    - "estimating and sampling graphs with multidimensional random walks"
    - "weak ties subtle role of information diffusion in online social networks"
    - "rhythms of social interaction messaging within a massive online network"

Connected through hyperedge HE-2 (induced by source paper "a game theoretic model for the formation of navigable small world networks the balance between distance and reciprocity"):
  with members:
    - "evolution of social attribute networks measurements modeling and implications using google"
    - "uncovering social network sybils in the wild"
    - "networks become navigable as nodes move and forget"
    - "the evolution of navigable small world networks"

Connected through hyperedge HE-3 (induced by source paper "geotagging one hundred million twitter accounts with total variation minimization"):
  with members:
    - "geo located twitter as proxy for global mobility patterns"
    - "home location identification of twitter users"
    - "a method based on total variation for network modularity optimization using the mbo scheme"
    - "parallel coordinate descent for l1 regularized loss minimization"

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)