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 "do altmetrics correlate with the quality of papers a large scale empirical study based on f1000prime data"):
  Abstract: In this study, we address the question whether (and to what extent, respectively) altmetrics are related to the scientific quality of papers (as measured by peer assessments). Only a few studies have previously investigated the relationship between altmetrics and assessments by peers. In the first step, we analyse the underlying dimensions of measurement for traditional metrics (citation counts) and altmetrics–by using principal component analysis (PCA) and factor analysis (FA). In the second step, we test the relationship between the dimensions and quality of papers (as measured by the post-publication peer-review system of F1000Prime assessments)–using regression analysis. The results of the PCA and FA show that altmetrics operate along different dimensions, whereas Mendeley counts are related to citation counts, and tweets form a separate dimension. The results of the regression analysis indicate that citation-based metrics and readership counts are significantly more related to quality, than tweets. This result on the one hand questions the use of Twitter counts for research evaluation purposes and on the other hand indicates potential use of Mendeley reader counts.

Includes members:
  Member "allegation of scientific misconduct increases twitter attention":
    also connected through other hyperedges:
      (none)
  Member "normalization of zero inflated data an empirical analysis of a new indicator family and its use with altmetrics data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "do altmetrics assess societal impact in a comparable way to case studies an empirical test of the convergent validity of altmetrics based on data from the uk research excellence framework ref")
  Member "grand challenges in altmetrics heterogeneity data quality and dependencies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "scholarly use of social media and altmetrics a review of the literature":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "social media in scholarly communication":
    also connected through other hyperedges:
      (none)
  Member "validity of altmetrics data for measuring societal impact a study using data from altmetric and f1000prime":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "do altmetrics assess societal impact in a comparable way to case studies an empirical test of the convergent validity of altmetrics based on data from the uk research excellence framework ref")
  Member "regression for citation data an evaluation of different methods":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the citation advantage of linking publications to research data")
  Member "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)