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 "fake news a survey of research detection methods and opportunities"):
  Abstract: The explosive growth in fake news and its erosion to democracy, justice, and public trust has increased the demand for fake news analysis, detection and intervention. This survey comprehensively and systematically reviews fake news research. The survey identifies and specifies fundamental theories across various disciplines, e.g., psychology and social science, to facilitate and enhance the interdisciplinary research of fake news. Current fake news research is reviewed, summarized and evaluated. These studies focus on fake news from four perspective: (1) the false knowledge it carries, (2) its writing style, (3) its propagation patterns, and (4) the credibility of its creators and spreaders. We characterize each perspective with various analyzable and utilizable information provided by news and its spreaders, various strategies and frameworks that are adaptable, and techniques that are applicable. By reviewing the characteristics of fake news and open issues in fake news studies, we highlight some potential research tasks at the end of this survey.

Includes members:
  Member "studying fake news via network analysis detection and mitigation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mining disinformation and fake news concepts methods and recent advancements")
  Member "the rise of guardians fact checking url recommendation to combat fake news":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "attributed multi relational attention network for fact checking url recommendation")
  Member "linknbed multi graph representation learning with entity linkage":
    also connected through other hyperedges:
      (none)
  Member "fakedetector effective fake news detection with deep diffusive neural network":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hgat hierarchical graph attention network for fake news detection")
  Member "belittling the source trustworthiness indicators to obfuscate fake news on the web":
    also connected through other hyperedges:
      (none)
  Member "the spread of low credibility content by social bots":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "topology comparison of twitter diffusion networks effectively reveals misleading information")
  Member "ti cnn convolutional neural networks for fake news detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "safe similarity aware multi modal fake news detection")
  Member "clickbait detection in tweets using self attentive network":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "federated hierarchical hybrid networks for clickbait 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)