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: "a practical approach to language complexity a wikipedia case study"
  Abstract: In this paper we present statistical analysis of English texts from Wikipedia. We try to address the issue of language complexity empirically by comparing the simple English Wikipedia (Simple) to comparable samples of the main English Wikipedia (Main). Simple is supposed to use a more simplified language with a limited vocabulary, and editors are explicitly requested to follow this guideline, yet in practice the vocabulary richness of both samples are at the same level. Detailed analysis of longer units (n-grams of words and part of speech tags) shows that the language of Simple is less complex than that of Main primarily due to the use of shorter sentences, as opposed to drastically simplified syntax or vocabulary. Comparing the two language varieties by the Gunning readability index supports this conclusion. We also report on the topical dependence of language complexity, that is, that the language is more advanced in conceptual articles compared to person-based (biographical) and object-based articles. Finally, we investigate the relation between conflict and language complexity by analyzing the content of the talk pages associated to controversial and peacefully developing articles, concluding that controversy has the effect of reducing language complexity.

Connected through hyperedge HE-1 (induced by source paper "a standardized project gutenberg corpus for statistical analysis of natural language and quantitative linguistics"):
  with members:
    - "natural language statistical features of lstm generated texts"
    - "mapping the americanization of english in space and time"
    - "in narrative texts punctuation marks obey the same statistics as words"
    - "quantifying structure differences in literature using symbolic diversity and entropy criteria"
    - "the emotional arcs of stories are dominated by six basic shapes"
    - "text mixing shapes the anatomy of rank frequency distributions"
    - "rank diversity of languages generic behavior in computational linguistics"
    - "collaborative tagging and semiotic dynamics"

Connected through hyperedge HE-2 (induced by source paper "robust clustering of languages across wikipedia growth"):
  with members:
    - "the evolution of wikipedia s norm network"
    - "understanding editing behaviors in multilingual wikipedia"
    - "trend of narratives in the age of misinformation"
    - "interactions of cultures and top people of wikipedia from ranking of 24 language editions"

Connected through hyperedge HE-3 (induced by source paper "understanding editing behaviors in multilingual wikipedia"):
  with members:
    - "cross language wikipedia editing of okinawa japan"
    - "multilinguals and wikipedia editing"
    - "ranking of wikipedia articles in search engines revisited fair ranking for reasonable quality"
    - "the tower of babel meets web 2 0 user generated content and its applications in a multilingual context"

Connected through hyperedge HE-4 (induced by source paper "comparing the topological properties of real and artificially generated scientific manuscripts"):
  with members:
    - "patterns of text reuse in a scientific corpus"
    - "probing the topological properties of complex networks modeling short written texts"
    - "a systematic comparison of supervised classifiers"
    - "measuring structural distances between texts"
    - "discriminating word senses with tourist walks in complex networks"
    - "scientific impact evaluation and the effect of self citations mitigating the bias by discounting h index"
    - "the similarity metric"

Connected through hyperedge HE-5 (induced by source paper "highlighting entanglement of cultures via ranking of multilingual wikipedia articles"):
  with members:
    - "spectral properties of google matrix of wikipedia and other networks"
    - "toward two dimensional search engines"
    - "biographical social networks on wikipedia a cross cultural study of links that made history"
    - "there is no deadline time evolution of wikipedia discussions"
    - "towards physical laws for software architecture"
    - "two dimensional ranking of wikipedia articles"

Connected through hyperedge HE-6 (induced by source paper "temporal analysis of activity patterns of editors in collaborative mapping project of openstreetmap"):
  with members:
    - "analyzing the performance of lru caches under non stationary traffic patterns"
    - "on the bursty evolution of online social networks"
    - "rhythms of social interaction messaging within a massive online network"

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)