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 "wikipedia cultural diversity dataset a complete cartography for 300 language editions"):
  Abstract: In this paper we present the Wikipedia Cultural Diversity dataset. For each existing Wikipedia language edition, the dataset contains a classification of the articles that represent its associated cultural context, i.e. all concepts and entities related to the language and to the territories where it is spoken. We describe the methodology we employed to classify articles, and the rich set of features that we defined to feed the classifier, and that are released as part of the dataset. We present several purposes for which we envision the use of this dataset, including detecting, measuring and countering content gaps in the Wikipedia project, and encouraging cross-cultural research in the field of digital humanities.

Includes members:
  Member "why the world reads wikipedia beyond english speakers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "quantifying engagement with citations on wikipedia")
  Member "understanding editing behaviors in multilingual wikipedia":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards better understanding researcher strategies in cross lingual event analytics")
  Member "multilinguals and wikipedia editing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "missing movie synergistic completion across multiple isomeric online movie knowledge libraries")
  Member "notes on noise contrastive estimation and negative sampling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improving textual network embedding with global attention via optimal transport")
  Member "the tower of babel meets web 2 0 user generated content and its applications in a multilingual context":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "measuring the importance of user generated content to search engines")
  Member "wikipedia based semantic interpretation for natural language processing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "eliminating search intent bias in learning to rank")

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.CY(Computers and Society)