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 "the structure and evolution of an offline peer to peer financial network"):
  Abstract: In this work, we investigate the structure and evolution of a peer-to-peer (P2P) payment application. A unique aspect of the network under consideration is that the edges among nodes represent financial transactions among individuals who shared an offline social interaction. Our dataset comes from Venmo, the most popular P2P mobile payment service. We present a series of static and dynamic measurements that summarize the key aspects of any social network, namely the degree distribution, density and connectivity. We find that the degree distributions do not follow a power-law distribution, confirming previous studies that real-world social networks are rarely scale-free. The giant component of Venmo is eventually composed of 99.9% of all nodes, and its clustering coefficient reaches 0.2. Last, we examine the "topological" version of the small-world hypothesis and find that Venmo users are separated by a mean of 5.9 steps and a median of 6 steps.

Includes members:
  Member "mind your credit assessing the health of the ripple credit network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "detecting mixing services via mining bitcoin transaction network with hybrid motifs")
  Member "evolution of social attribute networks measurements modeling and implications using google":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "defending against machine learning based inference attacks via adversarial examples opportunities and challenges")
  Member "four degrees of separation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "diffusion improves graph learning")

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)