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 "the geometry and topology of data and information for analytics of processes and behaviours building on bourdieu and addressing new societal challenges"):
  Abstract: We begin by summarizing the relevance and importance of inductive analytics based on the geometry and topology of data and information. Contemporary issues are then discussed. These include how sampling data for representativity is increasingly to be questioned. While we can always avail of analytics from a "bag of tools and techniques", in the application of machine learning and predictive analytics, nonetheless we present the case for Bourdieu and Benzecri-based science of data, as follows. This is to construct bridges between data sources and position-taking, and decision-making. There is summary presentation of a few case studies, illustrating and exemplifying application domains.

Includes members:
  Member "contextualizing geometric data analysis and related data analytics a virtual microscope for big data analytics":
    also connected through other hyperedges:
      (none)
  Member "sparse p adic data coding for computationally efficient and effective big data analytics":
    also connected through other hyperedges:
      (none)
  Member "computational properties of fiction writing and collaborative work":
    also connected through other hyperedges:
      (none)
  Member "the correspondence analysis platform for uncovering deep structure in data and information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "qualitative judgement of research impact domain taxonomy as a fundamental framework for judgement of the quality of research")
  Member "the structure of narrative the case of film scripts":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "computational properties of fiction writing and collaborative work")

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)