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 "detecting fake news with capsule neural networks"):
  Abstract: Fake news is dramatically increased in social media in recent years. This has prompted the need for effective fake news detection algorithms. Capsule neural networks have been successful in computer vision and are receiving attention for use in Natural Language Processing (NLP). This paper aims to use capsule neural networks in the fake news detection task. We use different embedding models for news items of different lengths. Static word embedding is used for short news items, whereas non-static word embeddings that allow incremental up-training and updating in the training phase are used for medium length or large news statements. Moreover, we apply different levels of n-grams for feature extraction. Our proposed architectures are evaluated on two recent well-known datasets in the field, namely ISOT and LIAR. The results show encouraging performance, outperforming the state-of-the-art methods by 7.8% on ISOT and 3.1% on the validation set, and 1% on the test set of the LIAR dataset.

Includes members:
  Member "fast capsnet for lung cancer screening":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "examining the benefits of capsule neural networks")
  Member "brain tumor type classification via capsule networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secure and robust machine learning for healthcare a survey")
  Member "information aggregation via dynamic routing for sequence encoding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic past and future for neural machine translation")
  Member "zero shot user intent detection via capsule neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "relation module for non answerable prediction on question answering")
  Member "fake news detection in social networks via crowd signals":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "attributed multi relational attention network for fact checking url recommendation")
  Member "liar liar pants on fire a new benchmark dataset for fake news detection":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "this just in fake news packs a lot in title uses simpler repetitive content in text body more similar to satire than real news":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a feature driven approach for identifying pathogenic social media accounts")
  Member "dynamic routing between capsules":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lightweight residual densely connected convolutional neural network")

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)