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 "clickbait in education positive or negative machine learning answers"):
  Abstract: The topic of clickbait has garnered lot of attention since the advent of social media. Meriam-Webster defines Clickbait as something designed to make readers want to click on a hyperlink especially when the link leads to content of dubious value or interest. Clickbait is used synonymously with terms with negative connotations such as yellow journalism, tabloid news etc. Majority of the work in this area has focused on detecting clickbait to stop being presented to the reader. In this work, we look at clickbait in the field of education with emphasis on educational videos that are authored by individual authors without any institutional backing. Such videos can become quite popular with different audiences and are not verified by any expert. We present findings that despite the negative connotation associated with clickbait, audiences value content regardless of the clickbait techniques and have an overall favorable impression. We also establish initial metrics that can be used to gauge the likeness factor for such educational videos/MOOCs.

Includes members:
  Member "natural language processing sentiment analysis and clinical analytics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "byod personal area networks pans and iot threats to patients privacy")
  Member "characterizing iomt personal area networks landscape":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "byod personal area networks pans and iot threats to patients privacy")
  Member "making a case for social media corpus for detecting depression":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "byod personal area networks pans and iot threats to patients privacy")
  Member "byod personal area networks pans and iot threats to patients privacy":
    also connected through other hyperedges:
      (none)
  Member "big data and social medical sciences state of the art and future trends":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "byod personal area networks pans and iot threats to patients privacy")
  Member "clickbait detection in tweets using self attentive network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "federated hierarchical hybrid networks for clickbait detection")
  Member "stop clickbait detecting and preventing clickbaits in online news media":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the chameleon attack manipulating content display in online social media")

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)