human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "measure the similarity of nodes in the complex networks"):
  Abstract: Measure the similarity of the nodes in the complex networks have interested many researchers to explore it. In this paper, a new method which is based on the degree centrality and the Relative-entropy is proposed to measure the similarity of the nodes in the complex networks. The results in this paper show that, the nodes which have a common structure property always have a high similarity to others nodes. The nodes which have a high influential to others always have a small value of similarity to other nodes and the marginal nodes also have a low similar to other nodes. The results in this paper show that the proposed method is useful and reasonable to measure the similarity of the nodes in the complex networks.

Includes members:
  Member "tsallis information dimension of complex networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tsallis entropy of complex networks")
  Member "on facebook most ties are weak":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the history of digital spam")
  Member "local structure entropy of complex networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stability of local information based centrality measurements under degree preserving randomizations")
  Member "a new information dimension of complex networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tsallis entropy of complex networks")
  Member "traveling trends social butterflies or frequent fliers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hashtag usage in a geographically local microblogging app")
  Member "analyzing user behavior across social sharing environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "latent space model for multi modal social data")
  Member "a large scale community structure analysis in facebook":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "uncovering complex overlapping pattern of communities in large scale social networks")

Question: Please tell me which class the source paper 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)