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 "active sensing of social networks"):
  Abstract: This paper develops an active sensing method to estimate the relative weight (or trust) agents place on their neighbors’ information in a social network. The model used for the regression is based on the steady state equation in the linear DeGroot model under the influence of stubborn agents; i.e., agents whose opinions are not influenced by their neighbors. This method can be viewed as a  social RADAR , where the stubborn agents excite the system and the latter can be estimated through the reverberation observed from the analysis of the agents’ opinions. The social network sensing problem can be interpreted as a blind compressed sensing problem with a sparse measurement matrix. We prove that the network structure will be revealed when a sufficient number of stubborn agents independently influence a number of ordinary (non-stubborn) agents. We investigate the scenario with a deterministic or randomized DeGroot model and propose a consistent estimator of the steady states for the latter scenario. Simulation results on synthetic and real world networks support our findings.

Includes members:
  Member "signal processing on graphs modeling causal relations in big data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards stationary time vertex signal processing")
  Member "the social system identification problem":
    also connected through other hyperedges:
      (none)
  Member "analysis and control of beliefs in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the social system identification problem")
  Member "graph theoretic distributed inference in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the controllability of clustered scale free networks")
  Member "ergodic randomized algorithms and dynamics over networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "opinion dynamics on correlated subjects in social networks")
  Member "opinion fluctuations and disagreement in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "shifting opinions in a social network through leader selection")
  Member "social structure of facebook networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "compressive sensing for cut improvement and local clustering")
  Member "a unique nonnegative solution to an underdetermined system from vectors to matrices":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "machine learning for geometrically consistent angular spread function estimation in massive mimo")

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)