human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "interactive sensing and decision making in social networks"
  Abstract: The proliferation of social media such as real time microblogging and online reputation systems facilitate real time sensing of social patterns and behavior. In the last decade, sensing and decision making in social networks have witnessed significant progress in the electrical engineering, computer science, economics, finance, and sociology research communities. Research in this area involves the interaction of dynamic random graphs, socio-economic analysis, and statistical inference algorithms. This monograph provides a survey, tutorial development, and discussion of four highly stylized examples: social learning for interactive sensing; tracking the degree distribution of social networks; sensing and information diffusion; and coordination of decision making via game-theoretic learning. Each of the four examples is motivated by practical examples, and comprises of a literature survey together with careful problem formulation and mathematical analysis. Despite being highly stylized, these examples provide a rich variety of models, algorithms and analysis tools that are readily accessible to a signal processing, control/systems theory, and applied mathematics audience.

Connected through hyperedge HE-1 (induced by source paper "information diffusion in social networks friendship paradox based models and statistical inference"):
  with members:
    - "what do your friends think efficient polling methods for networks using friendship paradox"
    - "centrality friendship paradoxes when our friends are more important than us"
    - "conjoining uncooperative societies facilitates evolution of cooperation"
    - "contagions in social networks effects of monophilic contagion friendship paradox and reactive networks"
    - "which friends are more popular than you contact strength and the friendship paradox in social networks"
    - "influence maximization over markovian graphs a stochastic optimization approach"
    - "engagement dynamics and sensitivity analysis of youtube videos"
    - "the majority illusion in social networks"

Connected through hyperedge HE-2 (induced by source paper "interplay between topology and social learning over weak graphs"):
  with members:
    - "local tomography of large networks under the low observability regime"
    - "consistent tomography under partial observations over adaptive networks"
    - "social learning over weakly connected graphs"
    - "euclidean distance matrices essential theory algorithms and applications"
    - "information exchange and learning dynamics over weakly connected adaptive networks"

Connected through hyperedge HE-3 (induced by source paper "influence maximization over markovian graphs a stochastic optimization approach"):
  with members:
    - "what do your friends think efficient polling methods for networks using friendship paradox"
    - "scalable methods for adaptively seeding a social network"
    - "exact recovery in the stochastic block model"
    - "influence maximization in continuous time diffusion networks"
    - "uncovering the temporal dynamics of diffusion networks"
    - "information spreading in stationary markovian evolving graphs"

Connected through hyperedge HE-4 (induced by source paper "the impact of random actions on opinion dynamics"):
  with members:
    - "opinion fluctuations and disagreement in social networks"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-5 (induced by source paper "social learning over weakly connected graphs"):
  with members:
    - "data falsification attacks on consensus based detection systems"
    - "information exchange and learning dynamics over weakly connected adaptive networks"
    - "higher dimensional consensus learning in large scale networks"

Connected through hyperedge HE-6 (induced by source paper "reinforcement learning and nonparametric detection of game theoretic equilibrium play in social networks"):
  with members:
    - "diffusion strategies outperform consensus strategies for distributed estimation over adaptive networks"
    - "game theory and the frequency selective interference channel"

Connected through hyperedge HE-7 (induced by source paper "rssi based distributed self localization for wireless sensor networks used in precision agriculture"):
  with members:
    - "distributed maximum likelihood sensor network localization"

Connected through hyperedge HE-8 (induced by source paper "information diffusion in social sensing"):
  with members:
    - "forecasting popularity of videos in youtube"
    - "loopy belief propagation for approximate inference an empirical study"
    - "removal of data incest in multi agent social learning in social networks"
    - "early stage influenza detection from twitter"
    - "twitter mood predicts the stock market"

Question: Please tell me which class the center node 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)