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: "slpa uncovering overlapping communities in social networks via a speaker listener interaction dynamic process"
  Abstract: Overlap is one of the characteristics of social networks, in which a person may belong to more than one social group. For this reason, discovering overlapping structures is necessary for realistic social analysis. In this paper, we present a novel, general framework to detect and analyze both individual overlapping nodes and entire communities. In this framework, nodes exchange labels according to dynamic interaction rules. A specific implementation called Speaker-listener Label Propagation Algorithm (SLPA1) demonstrates an excellent performance in identifying both overlapping nodes and overlapping communities with different degrees of diversity.

Connected through hyperedge HE-1 (induced by source paper "self falsifiable hierarchical detection of overlapping communities on social networks"):
  with members:
    - "gemsec graph embedding with self clustering"
    - "hidden community detection in social networks"
    - "the ground truth about metadata and community detection in networks"
    - "community detection in networks with unequal groups"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "spectral redemption in clustering sparse networks"
    - "demon a local first discovery method for overlapping communities"
    - "percolation computation in complex networks"

Connected through hyperedge HE-2 (induced by source paper "daoc stable clustering of large networks"):
  with members:
    - "bridging the gap between community and node representations graph embedding via community detection"
    - "accuracy evaluation of overlapping and multi resolution clustering algorithms on large datasets"
    - "consensus community detection in multilayer networks using parameter free graph pruning"
    - "clubmark a parallel isolation framework for benchmarking and profiling clustering algorithms on numa architectures"
    - "equivalence between modularity optimization and maximum likelihood methods for community detection"
    - "fuzzy overlapping community quality metrics"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-3 (induced by source paper "predicting complex user behavior from cdr based social networks"):
  with members:
    - "behavior revealed in mobile phone usage predicts loan repayment"
    - "community detection using a neighborhood strength driven label propagation algorithm"

Connected through hyperedge HE-4 (induced by source paper "weighted label propagation algorithm based on local edge betweenness"):
  with members:
    - "overlapping community detection in networks the state of the art and comparative study"

Connected through hyperedge HE-5 (induced by source paper "community detection in partially observable social networks"):
  with members:
    - "provable and practical approximations for the degree distribution using sublinear graph samples"
    - "overlapping community detection using neighborhood inflated seed expansion"
    - "overlapping community detection in networks the state of the art and comparative study"
    - "community detection in networks with node attributes"
    - "estimation of simultaneously sparse and low rank matrices"
    - "structure and overlaps of communities in networks"
    - "defining and evaluating network communities based on ground truth"
    - "finding missing edges and communities in incomplete networks"

Connected through hyperedge HE-6 (induced by source paper "high quality disjoint and overlapping community structure in large scale complex networks"):
  with members:
    - "dynamic structural similarity on graphs"
    - "personalized pagerank estimation and search a bidirectional approach"
    - "improving pagerank for local community detection"
    - "uncovering the small community structure in large networks a local spectral approach"
    - "leveraging disjoint communities for detecting overlapping community structure"
    - "heat kernel based community detection"
    - "community detection via local dynamic interaction"

Connected through hyperedge HE-7 (induced by source paper "an enhanced multi objective biogeography based optimization algorithm for automatic detection of overlapping communities in a social network with node attributes"):
  with members:
    - "evaluating the effect of topic consideration in identifying communities of rating based social networks"
    - "partitioning networks with node attributes by compressing information flow"
    - "structure and overlaps of communities in networks"
    - "towards linear time overlapping community detection in social networks"
    - "empirical comparison of algorithms for network community detection"
    - "detect overlapping and hierarchical community structure in networks"

Connected through hyperedge HE-8 (induced by source paper "a survey on influence maximization in a social network"):
  with members:
    - "modeling information diffusion in social networks"
    - "information diffusion in social networks in two phases"
    - "stop and stare optimal sampling algorithms for viral marketing in billion scale networks"
    - "parameterized approximability of maximizing the spread of influence in networks"
    - "latency bounded target set selection in social networks"
    - "on budgeted influence maximization in social networks"

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)