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 "on the heterogeneous distributions in paper citations"):
  Abstract: Academic papers have been the protagonists in disseminating expertise. Naturally, paper citation pattern analysis is an efficient and essential way of investigating the knowledge structure of science and technology. For decades, it has been observed that citation of scientific literature follows a heterogeneous and heavy-tailed distribution, and many of them suggest a power-law distribution, log-normal distribution, and related distributions. However, many studies are limited to small-scale approaches; therefore, it is hard to generalize. To overcome this problem, we investigate 21 years of citation evolution through a systematic analysis of the entire citation history of 42,423,644 scientific literatures published from 1996 to 2016 and contained in SCOPUS. We tested six candidate distributions for the scientific literature in three distinct levels of Scimago Journal & Country Rank (SJR) classification scheme. First, we observe that the raw number of annual citation acquisitions tends to follow the log-normal distribution for all disciplines, except for the first year of the publication. We also find significant disparity between the yearly acquired citation number among the journals, which suggests that it is essential to remove the citation surplus inherited from the prestige of the journals. Our simple method for separating the citation preference of an individual article from the inherited citation of the journals reveals an unexpected regularity in the normalized annual acquisitions of citations across the entire field of science. Specifically, the normalized annual citation acquisitions have power-law probability distributions with an exponential cut-off of the exponents around 2.3, regardless of its publication and citation year. Our results imply that journal reputation has a substantial long-term impact on the citation.

Includes members:
  Member "skewness of citation impact data and covariates of citation distributions a large scale empirical analysis based on web of science data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "testing for universality of mendeley readership distributions")
  Member "citation count distributions for large monodisciplinary journals":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "evaluating research and researchers by the journal impact factor is it better than coin flipping")
  Member "citations indicators of quality the impact fallacy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "peer review versus bibliometrics which method better predicts the scholarly impact of publications")
  Member "large scale analysis of the accuracy of the journal classification systems of web of science and scopus":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a tale of two databases the use of web of science and scopus in academic papers")
  Member "predicting the long term citation impact of recent publications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "comparison of research productivity of italian and norwegian professors and universities")
  Member "a review of the literature on citation impact indicators":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data")
  Member "distributions for cited articles from individual subjects and years":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "how much research shared on facebook is hidden from public view a comparison of public and private online activity around plos one papers")
  Member "power laws in citation distributions evidence from scopus":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")

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.DL(Digital Libraries)