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 "identifying the sentiment styles of youtube s vloggers"):
  Abstract: Vlogs provide a rich public source of data in a novel setting. This paper examined the continuous sentiment styles employed in 27,333 vlogs using a dynamic intra-textual approach to sentiment analysis. Using unsupervised clustering, we identified seven distinct continuous sentiment trajectories characterized by fluctuations of sentiment throughout a vlog's narrative time. We provide a taxonomy of these seven continuous sentiment styles and found that vlogs whose sentiment builds up towards a positive ending are the most prevalent in our sample. Gender was associated with preferences for different continuous sentiment trajectories. This paper discusses the findings with respect to previous work and concludes with an outlook towards possible uses of the corpus, method and findings of this paper for related areas of research.

Includes members:
  Member "fever a large scale dataset for fact extraction and verification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the microsoft toolkit of multi task deep neural networks for natural language understanding")
  Member "automatic detection of fake news":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hgat hierarchical graph attention network for fake news detection")
  Member "towards end to end speech recognition with deep convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "model watermarking for image processing networks")
  Member "the emotional arcs of stories are dominated by six basic shapes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "shaping the narrative arc an information theoretic approach to collaborative dialogue")
  Member "very deep convolutional networks for end to end speech recognition":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "rpn a residual pooling network for efficient federated learning")
  Member "the untold story of the clones content agnostic factors that impact youtube video popularity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sunstar a cost effective multi server solution for reliable video delivery")

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.CL(Computation and Language)