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 "a survey on natural language processing for fake news detection"):
  Abstract: Fake news detection is a critical yet challenging problem in Natural Language Processing (NLP). The rapid rise of social networking platforms has not only yielded a vast increase in information accessibility but has also accelerated the spread of fake news. Given the massive amount of Web content, automatic fake news detection is a practical NLP problem required by all online content providers. This paper presents a survey on fake news detection. Our survey introduces the challenges of automatic fake news detection. We systematically review the datasets and NLP solutions that have been developed for this task. We also discuss the limits of these datasets and problem formulations, our insights, and recommended solutions.

Includes members:
  Member "all in one multi task learning for rumour verification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "two path deep semi supervised learning for timely fake news detection")
  Member "automated fact checking task formulations methods and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fact check worthiness detection as positive unlabelled learning")
  Member "fakenewsnet a data repository with news content social context and dynamic information for studying fake news on social media":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "ukp athene multi sentence textual entailment for claim verification":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "answering while summarizing multi task learning for multi hop qa with evidence extraction")
  Member "fever a large scale dataset for fact extraction and verification":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the microsoft toolkit of multi task deep neural networks for natural language understanding")
  Member "twowingos a two wing optimization strategy for evidential claim verification":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "enteval a holistic evaluation benchmark for entity representations")
  Member "liar liar pants on fire a new benchmark dataset for fake news detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "a stylometric inquiry into hyperpartisan and fake news":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "hgat hierarchical graph attention network for fake news detection")

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)