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: "labelrankt incremental community detection in dynamic networks via label propagation"
  Abstract: An increasingly important challenge in network analysis is efficient detection and tracking of communities in dynamic networks for which changes arrive as a stream. There is a need for algorithms that can incrementally update and monitor communities whose evolution generates huge realtime data streams, such as the Internet or on-line social networks. In this paper, we propose LabelRankT, an online distributed algorithm for detection of communities in large-scale dynamic networks through stabilized label propagation. Results of tests on real-world networks demonstrate that LabelRankT has much lower computational costs than other algorithms. It also improves the quality of the detected communities compared to dynamic detection methods and matches the quality achieved by static detection approaches. Unlike most of other algorithms which apply only to binary networks, LabelRankT works on weighted and directed networks, which provides a flexible and promising solution for real-world applications.

Connected through hyperedge HE-1 (induced by source paper "a fast and efficient incremental approach toward dynamic community detection"):
  with members:
    - "community discovery in dynamic networks a survey"
    - "design generation and validation of extreme scale power law graphs"
    - "streaming graph challenge stochastic block partition"
    - "parallel heuristics for scalable community detection"
    - "generalized louvain method for community detection in large networks"

Connected through hyperedge HE-2 (induced by source paper "distributed community detection via metastability of the 2 choices dynamics"):
  with members:
    - "pooling or sampling collective dynamics for electrical flow estimation"
    - "phase transition of the 2 choices dynamics on core periphery networks"
    - "the ants problem"
    - "limits for rumor spreading in stochastic populations"
    - "ignore or comply on breaking symmetry in consensus"
    - "distributed graph clustering and sparsification"
    - "average whenever you meet opportunistic protocols for community detection"
    - "a tight analysis of the parallel undecided state dynamics with two colors"

Connected through hyperedge HE-3 (induced by source paper "community discovery in dynamic networks a survey"):
  with members:
    - "stream graphs and link streams for the modeling of interactions over time"
    - "revealing evolutions in dynamical networks"
    - "the ground truth about metadata and community detection in networks"
    - "on the evaluation potential of quality functions in community detection for different contexts"
    - "a framework for the construction of generative models for mesoscale structure in multilayer networks"
    - "generative benchmark models for mesoscale structures in multilayer networks"
    - "enumerating maximal cliques in temporal graphs"
    - "using multiple criteria methods to evaluate community partitions"

Connected through hyperedge HE-4 (induced by source paper "dyperm maximizing permanence for dynamic community detection"):
  with members:
    - "modularity based dynamic community detection"
    - "permanence and community structure in complex networks"
    - "metrics for community analysis a survey"
    - "a real time detecting algorithm for tracking community structure of dynamic networks"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "intrinsically dynamic network communities"

Connected through hyperedge HE-5 (induced by source paper "olcpm an online framework for detecting overlapping communities in dynamic social networks"):
  with members:
    - "detecting criminal organizations in mobile phone networks"
    - "labelrank a stabilized label propagation algorithm for community detection in networks"
    - "community detection using a neighborhood strength driven label propagation algorithm"

Connected through hyperedge HE-6 (induced by source paper "on efficiently detecting overlapping communities over distributed dynamic graphs"):
  with members:
    - "towards linear time overlapping community detection in social networks"
    - "finding connected components on map reduce in logarithmic rounds"
    - "layered label propagation a multiresolution coordinate free ordering for compressing social networks"

Connected through hyperedge HE-7 (induced by source paper "ensemble based discovery of disjoint overlapping and fuzzy community structures in networks"):
  with members:
    - "ensemble based algorithms to detect disjoint and overlapping communities in networks"
    - "permanence and community structure in complex networks"
    - "metrics for community analysis a survey"
    - "think locally act locally detection of small medium sized and large communities in large networks"
    - "personalized pagerank solution paths"
    - "leveraging disjoint communities for detecting overlapping community structure"
    - "yasca a collective intelligence approach for community detection in complex networks"
    - "overlapping community detection in networks the state of the art and comparative study"

Connected through hyperedge HE-8 (induced by source paper "scalable temporal latent space inference for link prediction in dynamic social networks"):
  with members:
    - "tripartite graph clustering for dynamic sentiment analysis on social media"
    - "nonparametric link prediction in dynamic networks"
    - "computing a nonnegative matrix factorization provably"
    - "on the complexity of nonnegative matrix factorization"

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)