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: "tsallis information dimension of complex networks"
  Abstract: The fractal and self-similarity properties are revealed in many complex networks. The information dimension is a useful method to describe the fractal and self-similarity properties of the complex networks. In order to show the influence of different parts in the complex networks to the information dimension, we have proposed a new information dimension based on the Tsallis entropy namely the Tsallis information dimension. The proposed information dimension is changed according to the scale which is described by the nonextensivity parameter q, and it is inverse with the nonextensivity parameter q. The existing information dimension is a special case of the Tsallis information dimension when q=1. The Tsallis information dimension is a generalized information dimension of the complex networks.

Connected through hyperedge HE-1 (induced by source paper "measure the similarity of nodes in the complex networks"):
  with members:
    - "on facebook most ties are weak"
    - "local structure entropy of complex networks"
    - "a new information dimension of complex networks"
    - "traveling trends social butterflies or frequent fliers"
    - "analyzing user behavior across social sharing environments"
    - "a large scale community structure analysis in facebook"

Connected through hyperedge HE-2 (induced by source paper "tsallis entropy of complex networks"):
  with members:
    - "on facebook most ties are weak"
    - "a new information dimension of complex networks"
    - "analyzing user behavior across social sharing environments"
    - "a large scale community structure analysis in facebook"

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)