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 "a reliability based approach for influence maximization using the evidence theory"):
  Abstract: The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing campaign goes viral through social networks for example. In this paper, we propose an influence measure that combines many influence indicators. Besides, we consider the reliability of each influence indicator and we present a distance-based process that allows to estimate the reliability of each indicator. The proposed measure is defined under the framework of the theory of belief functions. Furthermore, the reliability-based influence measure is used with an influence maximization model to select a set of users that are able to maximize the influence in the network. Finally, we present a set of experiments on a dataset collected from Twitter. These experiments show the performance of the proposed solution in detecting social influencers with good quality.

Includes members:
  Member "two evidential data based models for influence maximization in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evidential positive opinion influence measures for viral marketing")
  Member "adaptive imputation of missing values for incomplete pattern classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "two evidential data based models for influence maximization in twitter")
  Member "maximizing positive opinion influence using an evidential approach":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "evidential positive opinion influence measures for viral marketing")
  Member "median evidential c means algorithm and its application to community detection":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "evidential positive opinion influence measures for viral marketing")
  Member "dynamic time warping distance for message propagation classification in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "evidential positive opinion influence measures for viral marketing")
  Member "a data based approach to social influence maximization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making")

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)