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 novel method for depicting academic disciplines through google scholar citations the case of bibliometrics"
  Abstract: This article describes a procedure to generate a snapshot of the structure of a specific scientific community and their outputs based on the information available in Google Scholar Citations (GSC). We call this method multifaceted analysis of disciplines through academic profiles (MADAP). The international community of researchers working in Bibliometrics, Scientometrics, Informetrics, Webometrics, and Altmetrics was selected as a case study. The records of the top 1000 most cited documents by these authors according to GSC were manually processed to fill any missing information and deduplicate fields like the journal titles and book publishers. The results suggest that it is feasible to use GSC and the MADAP method to produce an accurate depiction of the community of researchers working in Bibliometrics (both specialists and occasional researchers) and their publication habits (main publication venues such as journals and book publishers). Additionally, the wide document coverage of Google Scholar (specially books and book chapters) enables more comprehensive analyses of the documents published in a specific discipline than were previously possible with other citation indexes, finally shedding light on what until now had been a blind spot in most citation analyses.

Connected through hyperedge HE-1 (induced by source paper "author level metrics in the new academic profile platforms the online behaviour of the bibliometrics community"):
  with members:
    - "can we use google scholar to identify highly cited documents"
    - "do researchgate scores create ghost academic reputations"
    - "scholars on twitter who and how many are they"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "a review of the characteristics of 108 author level bibliometric indicators"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"
    - "do altmetrics point to the broader impact of research an overview of benefits and disadvantages of altmetrics"

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.DL(Digital Libraries)