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: "influence of study type on twitter activity for medical research papers"
  Abstract: Twitter has been identified as one of the most popular and promising altmetrics data sources, as it possibly reflects a broader use of research articles by the general public. Several factors, such as document age, scientific discipline, number of authors and document type, have been shown to affect the number of tweets received by scientific documents. The particular meaning of tweets mentioning scholarly papers is, however, not entirely understood and their validity as impact indicators debatable. This study contributes to the understanding of factors influencing Twitter popularity of medical papers investigating differences between medical study types. 162,830 documents indexed in Embase to a medical study type have been analysed for the study type specific tweet frequency. Meta-analyses, systematic reviews and clinical trials were found to be tweeted substantially more frequently than other study types, while all basic research received less attention than the average. The findings correspond well with clinical evidence hierarchies. It is suggested that interest from laymen and patients may be a factor in the observed effects.

Connected through 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"):
  with members:
    - "field and time normalization of data with many zeros an empirical analysis using citation and twitter data"
    - "normalization of zero inflated data an empirical analysis of a new indicator family and its use with altmetrics data"
    - "measuring field normalized impact of papers on specific societal groups an altmetrics study based on mendeley data"
    - "how many scientific papers are mentioned in policy related documents an empirical investigation using web of science and altmetric data"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "policy documents as sources for measuring societal impact how often is climate change research mentioned in policy related documents"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "validity of altmetrics data for measuring societal impact a study using data from altmetric and f1000prime"

Connected through hyperedge HE-2 (induced by source paper "scholarly twitter metrics"):
  with members:
    - "a systematic identification and analysis of scientists on twitter"
    - "grand challenges in altmetrics heterogeneity data quality and dependencies"
    - "botornot a system to evaluate social bots"
    - "scholarly use of social media and altmetrics a review of the literature"
    - "the rise of social bots"
    - "when is an article actually published an analysis of online availability publication and indexation dates"
    - "differences in personal and professional tweets of scholars"
    - "adapting sentiment analysis for tweets linking to scientific papers"

Connected through hyperedge HE-3 (induced by source paper "on the differences between citations and altmetrics an investigation of factors driving altmetrics vs citations for finnish articles"):
  with members:
    - "interpreting altmetrics viewing acts on social media through the lens of citation and social theories"

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)