human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "robustness of sentence length measures in written texts"):
  Abstract: Hidden structural patterns in written texts have been subject of considerable research in the last decades. In particular, mapping a text into a time series of sentence lengths is a natural way to investigate text structure. Typically, sentence length has been quantified by using measures based on the number of words and the number of characters, but other variations are possible. To quantify the robustness of different sentence length measures, we analyzed a database containing about five hundred books in English. For each book, we extracted six distinct measures of sentence length, including number of words and number of characters (taking into account lemmatization and stop words removal). We compared these six measures for each book by using i) Pearson's coefficient to investigate linear correlations; ii) Kolmogorov--Smirnov test to compare distributions; and iii) detrended fluctuation analysis (DFA) to quantify auto-correlations. We have found that all six measures exhibit very similar behavior, suggesting that sentence length is a robust measure related to text structure.

Includes members:
  Member "in narrative texts punctuation marks obey the same statistics as words":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "using word embeddings to improve the discriminability of co occurrence text networks")
  Member "compression and the origins of zipf s law for word frequencies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "polysemy and brevity versus frequency in language")
  Member "text mixing shapes the anatomy of rank frequency distributions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a standardized project gutenberg corpus for statistical analysis of natural language and quantitative linguistics")
  Member "modeling the average shortest path length in growth of word adjacency networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "linguistic data mining with complex networks a stylometric oriented approach")
  Member "punctuation effects in english and esperanto texts":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a joint text mining rank size investigation of the rhetoric structures of the us presidents speeches")
  Member "beyond word frequency bursts lulls and scaling in the temporal distributions of words":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "computational human dynamics")

Question: Please tell me which class the source paper 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)