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: "differences in personal and professional tweets of scholars"
  Abstract: Purpose – The purpose of this paper is to show that there were differences in the use of Twitter by professors at AAU schools. Affordance use differed between the personal and professional tweets of professors as categorized by turkers. Framing behaviors were described that could impact the interpretation of tweets by audience members. Design/methodology/approach – A three phase research design was used that included surveys of professors, categorization of tweets by workers in Amazon’s Mechanical Turk, and categorization of tweets by active professors on Twitter. Findings – There were significant differences found between professors that reported having a Twitter account, significant differences found between types of Twitter accounts (personal, professional, or both), and significant differences in the affordances used in personal and professional tweets. Framing behaviors were described that may assist altmetric researchers in distinguishing between personal and professional tweets. Research limitation...

Connected through hyperedge HE-1 (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"
    - "influence of study type on twitter activity for medical research papers"
    - "adapting sentiment analysis for tweets linking to scientific papers"

Connected through hyperedge HE-2 (induced by source paper "a systematic identification and analysis of scientists on twitter"):
  with members:
    - "astrophysicists on twitter an in depth analysis of tweeting and scientific publication behavior"
    - "studying social networks at scale macroscopic anatomy of the twitter social graph"
    - "do altmetrics correlate with citations extensive comparison of altmetric indicators with citations from a multidisciplinary perspective"
    - "alternative metrics in scientometrics a meta analysis of research into three altmetrics"
    - "do altmetrics point to the broader impact of research an overview of benefits and disadvantages of altmetrics"
    - "how well developed are altmetrics a cross disciplinary analysis of the presence of alternative metrics in scientific publications"
    - "tweeting biomedicine an analysis of tweets and citations in the biomedical literature"
    - "the role of twitter in the life cycle of a scientific publication"

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)