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 "a standardized project gutenberg corpus for statistical analysis of natural language and quantitative linguistics"):
  Abstract: The use of Project Gutenberg (PG) as a text corpus has been extremely popular in statistical analysis of language for more than 25 years. However, in contrast to other major linguistic datasets of similar importance, no consensual full version of PG exists to date. In fact, most PG studies so far either consider only a small number of manually selected books, leading to potential biased subsets, or employ vastly different pre-processing strategies (often specified in insufficient details), raising concerns regarding the reproducibility of published results. In order to address these shortcomings, here we present the Standardized Project Gutenberg Corpus (SPGC), an open science approach to a curated version of the complete PG data containing more than 50,000 books and more than $3 \times 10^9$ word-tokens. Using different sources of annotated metadata, we not only provide a broad characterization of the content of PG, but also show different examples highlighting the potential of SPGC for investigating language variability across time, subjects, and authors. We publish our methodology in detail, the code to download and process the data, as well as the obtained corpus itself on 3 different levels of granularity (raw text, timeseries of word tokens, and counts of words). In this way, we provide a reproducible, pre-processed, full-size version of Project Gutenberg as a new scientific resource for corpus linguistics, natural language processing, and information retrieval.

Includes members:
  Member "natural language statistical features of lstm generated texts":
    also connected through other hyperedges:
      (none)
  Member "mapping the americanization of english in space and time":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hahahahaha duuuuude yeeessss a two parameter characterization of stretchable words and the dynamics of mistypings and misspellings")
  Member "in narrative texts punctuation marks obey the same statistics as words":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "using word embeddings to improve the discriminability of co occurrence text networks")
  Member "quantifying structure differences in literature using symbolic diversity and entropy criteria":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "basis to develop a platform for multiple scale complex systems modeling and visualization monet")
  Member "the emotional arcs of stories are dominated by six basic shapes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "shaping the narrative arc an information theoretic approach to collaborative dialogue")
  Member "text mixing shapes the anatomy of rank frequency distributions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robustness of sentence length measures in written texts")
  Member "rank diversity of languages generic behavior in computational linguistics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "guiding the self organization of cyber physical systems")
  Member "a practical approach to language complexity a wikipedia case study":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robust clustering of languages across wikipedia growth")

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)