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: "mendeley readership as a filtering tool to identify highly cited publications"
  Abstract: This study presents a large-scale analysis of the distribution and presence of Mendeley readership scores over time and across disciplines. We study whether Mendeley readership scores (RS) can identify highly cited publications more effectively than journal citation scores (JCS). Web of Science (WoS) publications with digital object identifiers (DOIs) published during the period 2004–2013 and across five major scientific fields were analyzed. The main result of this study shows that RS are more effective (in terms of precision/recall values) than JCS to identify highly cited publications across all fields of science and publication years. The findings also show that 86.5% of all the publications are covered by Mendeley and have at least one reader. Also, the share of publications with Mendeley RS is increasing from 84% in 2004 to 89% in 2009, and decreasing from 88% in 2010 to 82% in 2013. However, it is noted that publications from 2010 onwards exhibit on average a higher density of readership versus citation scores. This indicates that compared to citation scores, RS are more prevalent for recent publications and hence they could work as an early indicator of research impact. These findings highlight the potential and value of Mendeley as a tool for scientometric purposes and particularly as a relevant tool to identify highly cited publications.

Connected through hyperedge HE-1 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications"):
  with members:
    - "scholarly twitter metrics"
    - "social media metrics for new research evaluation"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "using almetrics for contextualised mapping of societal impact from hits to networks"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"
    - "tweets as impact indicators examining the implications of automated bot accounts on twitter"
    - "do altmetrics point to the broader impact of research an overview of benefits and disadvantages of altmetrics"

Connected through hyperedge HE-2 (induced by source paper "mendeley reader counts for us computer science conference papers and journal articles"):
  with members:
    - "google scholar web of science and scopus a systematic comparison of citations in 252 subject categories"
    - "on the relationships between bibliographic characteristics of scientific documents and citation and mendeley readership counts a large scale analysis of web of science publications"
    - "could scientists use altmetric com scores to predict longer term citation counts"
    - "which type of citation analysis generates the most accurate taxonomy of scientific and technical knowledge"
    - "role of interdisciplinarity in computer sciences quantification impact and life trajectory"
    - "are the discretised lognormal and hooked power law distributions plausible for citation data"
    - "more precise methods for national research citation impact comparisons"
    - "tweets vs mendeley readers how do these two social media metrics differ"

Connected through hyperedge HE-3 (induced by source paper "can google scholar and mendeley help to assess the scholarly impacts of dissertations"):
  with members:
    - "google scholar web of science and scopus a systematic comparison of citations in 252 subject categories"
    - "on the relationships between bibliographic characteristics of scientific documents and citation and mendeley readership counts a large scale analysis of web of science publications"
    - "google scholar and the gray literature a reply to bonato s review"
    - "medical theses and derivative articles dissemination of contents and publication patterns"
    - "the precision of the arithmetic mean geometric mean and percentiles for citation data an experimental simulation modelling approach"
    - "the influence of time and discipline on the magnitude of correlations between citation counts and quality scores"
    - "tweets vs mendeley readers how do these two social media metrics differ"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"

Connected through hyperedge HE-4 (induced by source paper "social media metrics for new research evaluation"):
  with members:
    - "on the relationships between bibliographic characteristics of scientific documents and citation and mendeley readership counts a large scale analysis of web of science publications"
    - "towards the social media studies of science social media metrics present and future"
    - "scholars on twitter who and how many are they"
    - "three practical field normalised alternative indicator formulae for research evaluation"
    - "a systematic identification and analysis of scientists on twitter"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "t factor a metric for measuring impact on twitter"
    - "iran s scientific dominance and the emergence of south east asian countries as scientific collaborators in the persian gulf region"

Connected through hyperedge HE-5 (induced by source paper "on the relationships between bibliographic characteristics of scientific documents and citation and mendeley readership counts a large scale analysis of web of science publications"):
  with members:
    - "on the differences between citations and altmetrics an investigation of factors driving altmetrics vs citations for finnish articles"
    - "what makes papers visible on social media an analysis of various document characteristics"
    - "the discretised lognormal and hooked power law distributions for complete citation data best options for modelling and regression"
    - "national disciplinary and temporal variations in the extent to which articles with more authors have more impact evidence from a geometric field normalised citation indicator"
    - "interpreting altmetrics viewing acts on social media through the lens of citation and social theories"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "regression for citation data an evaluation of different methods"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"

Connected through hyperedge HE-6 (induced by source paper "social media attention increases article visits an investigation on article level referral data of peerj"):
  with members:
    - "the open access advantage considering citation article usage and social media attention"
    - "usage history of scientific literature nature metrics and metrics of nature publications"
    - "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"
    - "tweeting biomedicine an analysis of tweets and citations in the biomedical literature"
    - "exploring scientists working timetable do scientists often work overtime"
    - "altmetrics in the wild using social media to explore scholarly impact"
    - "a principal component analysis of 39 scientific impact measures"

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)