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 "consistent community detection in continuous time networks of relational events"):
  Abstract: In many application settings involving networks, such as messages between users of an on-line social network or transactions between traders in financial markets, the observed data are in the form of relational events with timestamps, which form a continuous-time network. We propose the Community Hawkes Independent Pairs (CHIP) model for community detection on such timestamped relational event data. We demonstrate that applying spectral clustering to adjacency matrices constructed from relational events generated by the CHIP model provides consistent community detection for a growing number of nodes. In particular, we obtain explicit non-asymptotic upper bounds on the misclustering rates based on the separation conditions required on the parameters of the model for consistent community detection. We also develop consistent and computationally efficient estimators for the parameters of the model. We demonstrate that our proposed CHIP model and estimation procedure scales to large networks with tens of thousands of nodes and provides superior fits compared to existing continuous-time network models on several real networks.

Includes members:
  Member "expecting to be hip hawkes intensity processes for social media popularity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nestpp modeling thread dynamics in online discussion forums")
  Member "the block point process model for continuous time event based dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "predicting dynamic embedding trajectory in temporal interaction networks")
  Member "stochastic block model and community detection in the sparse graphs a spectral algorithm with optimal rate of recovery":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "randomized spectral clustering in large scale stochastic block models")
  Member "seismic a self exciting point process model for predicting tweet popularity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "inf vae a variational autoencoder framework to integrate homophily and influence in diffusion prediction")
  Member "stochastic block transition models for dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a statistical model for dynamic networks with neural variational inference")
  Member "modeling events with cascades of poisson processes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a multi channel neural graphical event model with negative evidence")

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)