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 "simulating sir processes on networks using weighted shortest paths"):
  Abstract: We present a framework to simulate SIR processes on networks using weighted shortest paths. Our framework maps the SIR dynamics to weights assigned to the edges of the network, which can be done for Markovian and non-Markovian processes alike. The weights represent the propagation time between the adjacent nodes for a particular realization. We simulate the dynamics by constructing an ensemble of such realizations, which can be done by using a Markov Chain Monte Carlo method or by direct sampling. The former provides a runtime advantage when realizations from all possible sources are computed as the weighted shortest paths can be re-calculated more efficiently. We apply our framework to three empirical networks and analyze the expected propagation time between all pairs of nodes. Furthermore, we have employed our framework to perform efficient source detection and to improve strategies for time-critical vaccination.

Includes members:
  Member "measuring the potential of individual airports for pandemic spread over the world airline network":
    also connected through other hyperedges:
      (none)
  Member "identification of patient zero in static and temporal networks robustness and limitations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "approximate identification of the optimal epidemic source in complex networks")
  Member "fastsir algorithm a fast algorithm for the simulation of the epidemic spread in large networks by using the susceptible infected recovered compartment model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mapping spreading dynamics from time respecting shortest paths to bond percolation")
  Member "locating the source of diffusion in large scale networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "noisy source location on a line")
  Member "information contagion an empirical study of the spread of news on digg and twitter social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "modeling information diffusion in online social networks with partial differential equations")

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)