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 "folksonomication predicting tags for movies from plot synopses using emotion flow encoded neural network"):
  Abstract: Folksonomy of movies covers a wide range of heterogeneous information about movies, like the genre, plot structure, visual experiences, soundtracks, metadata, and emotional experiences from watching a movie. Being able to automatically generate or predict tags for movies can help recommendation engines improve retrieval of similar movies, and help viewers know what to expect from a movie in advance. In this work, we explore the problem of creating tags for movies from plot synopses. We propose a novel neural network model that merges information from synopses and emotion flows throughout the plots to predict a set of tags for movies. We compare our system with multiple baselines and found that the addition of emotion flows boosts the performance of the network by learning ~18\% more tags than a traditional machine learning system.

Includes members:
  Member "mpst a corpus of movie plot synopses with tags":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "letting emotions flow success prediction by modeling the flow of emotions in books")
  Member "the emotional arcs of stories are dominated by six basic shapes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "shaping the narrative arc an information theoretic approach to collaborative dialogue")
  Member "hierarchical attention networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "text classification algorithms a survey")
  Member "you re mr lebowski i m the dude inducing address term formality in signed social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "extraction and analysis of fictional character networks a survey")
  Member "recurrent models of visual attention":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "see more know more unsupervised video object segmentation with co attention siamese networks")
  Member "neural machine translation by jointly learning to align and translate":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "multiple object recognition with visual attention":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "neuroevolution of self interpretable agents")
  Member "from once upon a time to happily ever after tracking emotions in novels and fairy tales":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "shaping the narrative arc an information theoretic approach to collaborative dialogue")

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)