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 "sir hawkes linking epidemic models and hawkes processes to model diffusions in finite populations"):
  Abstract: Among the statistical tools for online information diffusion modeling, both epidemic models and Hawkes point processes are popular choices. The former originate from epidemiology, and consider information as a viral contagion which spreads into a population of online users. The latter have roots in geophysics and finance, view individual actions as discrete events in continuous time, and modulate the rate of events according to the self-exciting nature of event sequences. Here, we establish a novel connection between these two frameworks. Namely, the rate of events in an extended Hawkes model is identical to the rate of new infections in the Susceptible-Infected-Recovered (SIR) model after marginalizing out recovery events -- which are unobserved in a Hawkes process. This result paves the way to apply tools developed for SIR to Hawkes, and vice versa. It also leads to HawkesN, a generalization of the Hawkes model which accounts for a finite population size. Finally, we derive the distribution of cascade sizes for HawkesN, inspired by methods in stochastic SIR. Such distributions provide nuanced explanations to the general unpredictability of popularity: the distribution for diffusion cascade sizes tends to have two modes, one corresponding to large cascade sizes and another one around zero.

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 neural hawkes process a neurally self modulating multivariate point process":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "d ej a vu a contextualized temporal attention mechanism for sequential recommendation")
  Member "steering opinion dynamics in information diffusion networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the mass fake news and cognition security")
  Member "a stochastic differential equation framework for guiding online user activities in closed loop":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neural jump stochastic differential equations")
  Member "tideh time dependent hawkes process for predicting retweet dynamics":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "socialgrid a tcn enhanced method for online discussion forecasting")
  Member "feature driven and point process approaches for popularity prediction":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "nestpp modeling thread dynamics in online discussion forums")
  Member "exploring limits to prediction in complex social systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "popularity prediction on social platforms with coupled graph neural networks")
  Member "modeling and predicting popularity dynamics of microblogs using self excited hawkes processes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "socialgrid a tcn enhanced method for online discussion forecasting")

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)