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 "can we count on social media metrics first insights into the active scholarly use of social media"):
  Abstract: Measuring research impact is important for ranking publications in academic search engines and for research evaluation. Social media metrics or altmetrics measure the impact of scientific work based on social media activity. Altmetrics are complementary to traditional, citation-based metrics, e.g. allowing the assessment of new publications for which citations are not yet available. Despite the increasing importance of altmetrics, their characteristics are not well understood: Until now it has not been researched what kind of researchers are actively using which social media services and why - important questions for scientific impact prediction. Based on a survey among 3,430 scientists, we uncover previously unknown and significant differences between social media services: We identify services which attract young and experienced researchers, respectively, and detect differences in usage motivations. Our findings have direct implications for the future design of altmetrics for scientific impact prediction.

Includes members:
  Member "grand challenges in altmetrics heterogeneity data quality and dependencies":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "altmetrics chapter from beyond bibliometrics harnessing multidimensional indicators of scholarly impact":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "amplifying the impact of open access wikipedia and the diffusion of science")
  Member "do altmetrics point to the broader impact of research an overview of benefits and disadvantages of altmetrics":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the stability of twitter metrics a study on unavailable twitter mentions of scientific publications")
  Member "nltk the natural language toolkit":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sentencemim a latent variable language model")

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.SI(Social and Information Networks)