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 "coupon advertising in online social systems algorithms and sampling techniques"):
  Abstract: Online social systems have become important platforms for viral marketing where the advertising of products is carried out with the communication of users. After adopting the product, the seed buyers may spread the information to their friends via online messages e.g. posts and tweets. In another issue, electronic coupon system is one of the relevant promotion vehicles that help manufacturers and retailers attract more potential customers. By offering coupons to seed buyers, there is a chance to convince the influential users who are, however, at first not very interested in the product. In this paper, we propose a coupon based online influence model and consider the problem that how to maximize the profit by selecting appropriate seed buyers. The considered problem herein is markedly different from other influence related problems as its objective function is not monotone. We provide an algorithmic analysis and give several algorithms designed with different sampling techniques. In particular, we propose the RA-T and RA-S algorithms which are not only provably effective but also scalable on large datasets. The proposed theoretical results are evaluated by extensive experiments done on large-scale real-world social networks. The analysis of this paper also provides an algorithmic framework for non-monotone submodular maximization problems in social networks.

Includes members:
  Member "an efficient randomized algorithm for rumor blocking in online social networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "stop and stare optimal sampling algorithms for viral marketing in billion scale networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "time constrained adaptive influence maximization")
  Member "pricing strategies for viral marketing on social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "efficient approximation algorithms for adaptive target profit maximization")

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)