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 "self organizing flows in social networks"):
  Abstract: Social networks offer users new means of accessing information, essentially relying on "social filtering", i.e. propagation and filtering of information by social contacts. The sheer amount of data flowing in these networks, combined with the limited budget of attention of each user, makes it difficult to ensure that social filtering brings relevant content to interested users. Our motivation in this paper is to measure to what extent self-organization of a social network results in efficient social filtering.To this end we introduce flow games, a simple abstraction that models network formation under selfish dynamics, featuring user-specific interests and budget of attention. In the context of homogeneous user interests, we show that selfish dynamics converge to a stable network structure (namely a pure Nash equilibrium) with close-to-optimal information dissemination. We show that, in contrast, for the more realistic case of heterogeneous interests, selfish dynamics may lead to information dissemination that can be arbitrarily inefficient, as captured by an unbounded "price of anarchy".Nevertheless the situation differs when user interests exhibit a particular structure, captured by a metric space with low doubling dimension. In that case, natural autonomous dynamics converge to a stable configuration. Moreover, users obtain all the information of interest to them in the corresponding dissemination, provided their budget of attention is logarithmic in the size of their interest set.

Includes members:
  Member "tight bounds for rumor spreading with vertex expansion":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the capacity of smartphone peer to peer networks")
  Member "bounded budget connection bbc games or how to make friends and influence people on a budget":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "locality based network creation games")
  Member "acyclic preference systems in p2p networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "computational complexity of stable marriage and stable roommates and their variants")
  Member "fast construction of nets in low dimensional metrics and their applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a data dependent algorithm for querying earth mover s distance with low doubling dimension")

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)