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: "google or google examining the popularity of the new osn"
  Abstract: In an era when Facebook and Twitter dominate the market for social media, Google has made another attempt to become a player by introducing Google+ (G+). This begs the question that "whether G+ can sustain a meaningful growth to become a relevant player in this market despite the dominance of Facebook and Twitter?". The conflicting reports on G+ mostly focus on high level statistics that do not offer a meaningful answer. To tackle this question, this paper presents a detailed measurement study to characterize the key features of G+. Our results suggest that the short-term growth of G+ during its first 10 months far outpaced other OSNs. However, we do not observe a bandwagon effect (characteristic of other popular OSNs) in the growth of active users who represent 10.3% of the whole population. Furthermore, only 43.5% of G+ users form the largest connected component that has connectivity features similar to other popular OSNs. Finally, despite the small fraction of users that frequently visit G+, the aggregate daily activity has increased over 50% due to the dramatic growth in the total population of users.

Connected through hyperedge HE-1 (induced by source paper "evolution of social attribute networks measurements modeling and implications using google"):
  with members:
    - "multi scale dynamics in a massive online social network"
    - "constructing and sampling graphs with a prescribed joint degree distribution"
    - "predicting links and inferring attributes using a social attribute network san"
    - "four degrees of separation"
    - "multiplicative attribute graph model of real world networks"
    - "hyperanf approximating the neighbourhood function of very large graphs on a budget"
    - "systematic topology analysis and generation using degree correlations"

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.SI(Social and Information Networks)