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 "modeling memetics using edge diversity"):
  Abstract: The study of meme propagation and the prediction of meme trajectory are emerging areas of interest in the field of complex networks research. In addition to the properties of the meme itself, the structural properties of the underlying network decides the speed and the trajectory of the propagating meme. In this paper, we provide an artificial framework for studying the meme propagation patterns. Firstly, the framework includes a synthetic network which simulates a real world network and acts as a testbed for meme simulation. Secondly, we propose a meme spreading model based on the diversity of edges in the network. Through the experiments conducted, we show that the generated synthetic network combined with the proposed spreading model is able to simulate a real world meme spread. Our proposed model is validated by the propagation of the Higgs boson meme on Twitter as well as many real world social networks.

Includes members:
  Member "understanding spreading patterns on social networks based on network topology":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "estimating shell index in a graph with local information")
  Member "predicting successful memes using network and community structure":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a feature driven approach for identifying pathogenic social media accounts")
  Member "virality prediction and community structure in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep collaborative embedding for information cascade prediction")
  Member "exploring text virality in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "causal effects of brevity on style and success in social media")
  Member "the role of social networks in information diffusion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep learning approach on information diffusion in heterogeneous networks")
  Member "information contagion an empirical study of the spread of news on digg and twitter social networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)