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: "authorship recognition via fluctuation analysis of network topology and word intermittency"
  Abstract: Statistical methods have been widely employed in many practical natural language processing applications. More specifically, complex network concepts and methods from dynamical systems theory have been successfully applied to recognize stylistic patterns in written texts. Despite the large number of studies devoted to representing texts with physical models, only a few studies have assessed the relevance of attributes derived from the analysis of stylistic fluctuations. Because fluctuations represent a pivotal factor for characterizing a myriad of real systems, this study focused on the analysis of the properties of stylistic fluctuations in texts via topological analysis of complex networks and intermittency measurements. The results showed that different authors display distinct fluctuation patterns. In particular, it was found that it is possible to identify the authorship of books using the intermittency of specific words. Taken together, the results described here suggest that the patterns found in stylistic fluctuations could be used to analyze other related complex systems. Furthermore, the discovery of novel patterns related to textual stylistic fluctuations indicates that these patterns could be useful to improve the state of the art of many stylistic-based natural language processing tasks.

Connected through hyperedge HE-1 (induced by source paper "representation of texts as complex networks a mesoscopic approach"):
  with members:
    - "the emotional arcs of stories are dominated by six basic shapes"
    - "using complex networks for text classification discriminating informative and imaginative documents"
    - "a complex network approach to stylometry"
    - "modeling the average shortest path length in growth of word adjacency networks"
    - "authorship attribution through function word adjacency networks"
    - "word length entropies and correlations of natural language written texts"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-2 (induced by source paper "word sense disambiguation a complex network approach"):
  with members:
    - "a complex network approach to stylometry"
    - "probing the topological properties of complex networks modeling short written texts"
    - "comparing the topological properties of real and artificially generated scientific manuscripts"
    - "authorship attribution through function word adjacency networks"
    - "a systematic comparison of supervised classifiers"
    - "discriminating word senses with tourist walks in complex networks"
    - "structure semantics interplay in complex networks and its effects on the predictability of similarity in texts"

Connected through hyperedge HE-3 (induced by source paper "on the role of words in the network structure of texts application to authorship attribution"):
  with members:
    - "text authorship identified using the dynamics of word co occurrence networks"
    - "using complex networks for text classification discriminating informative and imaginative documents"
    - "probing the topological properties of complex networks modeling short written texts"
    - "authorship attribution through function word adjacency networks"
    - "stability and continuity of centrality measures in weighted graphs"
    - "a systematic comparison of supervised classifiers"
    - "structure semantics interplay in complex networks and its effects on the predictability of similarity in texts"

Connected through hyperedge HE-4 (induced by source paper "extractive multi document summarization using multilayer networks"):
  with members:
    - "using network science and text analytics to produce surveys in a scientific topic"
    - "concentric network symmetry grasps authors styles in word adjacency networks"
    - "a complex network approach to stylometry"
    - "comparing the topological properties of real and artificially generated scientific manuscripts"
    - "structure semantics interplay in complex networks and its effects on the predictability of similarity in texts"
    - "lexrank graph based lexical centrality as salience in text summarization"

Connected through hyperedge HE-5 (induced by source paper "authorship attribution based on life like network automata"):
  with members:
    - "concentric network symmetry grasps authors styles in word adjacency networks"
    - "a complex network approach to stylometry"
    - "authorship attribution through function word adjacency networks"
    - "a systematic comparison of supervised classifiers"
    - "structure semantics interplay in complex networks and its effects on the predictability of similarity in texts"

Connected through hyperedge HE-6 (induced by source paper "predicting language diversity with complex networks"):
  with members:
    - "a complex network approach to stylometry"
    - "modeling the average shortest path length in growth of word adjacency networks"
    - "diffusion of lexical change in social media"
    - "structure semantics interplay in complex networks and its effects on the predictability of similarity in texts"

Connected through hyperedge HE-7 (induced by source paper "enriching complex networks with word embeddings for detecting mild cognitive impairment from speech transcripts"):
  with members:
    - "authorship attribution based on life like network automata"
    - "sentence segmentation in narrative transcripts from neuropsychological tests using recurrent convolutional neural networks"
    - "enriching word vectors with subword information"
    - "a complex network approach to stylometry"
    - "inducing language networks from continuous space word representations"
    - "distributed representations of words and phrases and their compositionality"
    - "exploiting similarities among languages for machine translation"
    - "natural language processing almost from scratch"

Connected through hyperedge HE-8 (induced by source paper "labelled network subgraphs reveal stylistic subtleties in written texts"):
  with members:
    - "on the modeling of musical solos as complex networks"
    - "using complex networks for text classification discriminating informative and imaginative documents"
    - "authorship attribution via network motifs identification"
    - "a complex network approach to stylometry"
    - "probing the topological properties of complex networks modeling short written texts"
    - "authorship attribution using word network features"
    - "structure semantics interplay in complex networks and its effects on the predictability of similarity in texts"
    - "measuring the evolution of contemporary western popular music"

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.CL(Computation and Language)