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 "how to go viral cheaply and quickly"):
  Abstract: Given a social network represented by a graph G, we consider the problem of finding a bounded cardinality set of nodes S with the property that the influence spreading from S in G is as large as possible. The dynamics that govern the spread of influence is the following: initially only elements in S are influenced; subsequently at each round, the set of influenced elements is augmented by all nodes in the network that have a sufficiently large number of already influenced neighbors. While it is known that the general problem is hard to solve — even in the approximate sense — we present exact polynomial time algorithms for trees, paths, cycles, and complete graphs.

Includes members:
  Member "parameterized approximability of maximizing the spread of influence in networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parameterized approximation schemes for independent set of rectangles and geometric knapsack")
  Member "latency bounded target set selection in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "time bounded influence diffusion with incentives")
  Member "influence diffusion in social networks under time window constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "time bounded influence diffusion with incentives")
  Member "contagious sets in expanders":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "time bounded influence diffusion with incentives")
  Member "target set selection problem for honeycomb networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "inapproximability and parameterized results for the target set selection problem")

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)