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 "properties of erd h o s r enyi graphs"):
  Abstract: We study graph properties, such as diameter, density and clustering coefficients, and the relationships between these graph properties. Whereas for graphs on small number of vertices we can exactly compute the average values and range for each property of interest, this becomes infeasible for larger graphs. Thus, we analyze graph properties and the relationships between the properties using Erdős-Renyi graphs, which model well the underlying graph space. Specifically, we focus on thirteen properties of interest in graph theory and graph mining. We numerically study the behavior of these properties, as the number of vertices increase, for the Erdős-Renyi model and compare the results with known theoretical bounds, where applicable. We also use linear and non-linear models to predict a specific property based on the other properties.

Includes members:
  Member "same stats different graphs exploring the space of graphs in terms of graph properties":
    also connected through other hyperedges:
      (none)
  Member "a comprehensive survey on graph neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on the expressive power of graph neural networks")
  Member "privacy preserving social network publication against mutual friend attacks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "same stats different graphs exploring the space of graphs in terms of graph properties")

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)