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 "the mass fake news and cognition security"):
  Abstract: The wide spread of fake news in social networks is posing threats to social stability, economic development and political democracy etc. Numerous studies have explored the effective detection approaches of online fake news, while few works study the intrinsic propagation and cognition mechanisms of fake news. Since the development of cognitive science paves a promising way for the prevention of fake news, we present a new research area called Cognition Security (CogSec), which studies the potential impacts of fake news to human cognition, ranging from misperception, untrusted knowledge acquisition, targeted opinion/attitude formation, to biased decision making, and investigates the effective ways for fake news debunking. CogSec is a multidisciplinary research field that leverages knowledge from social science, psychology, cognition science, neuroscience, AI and computer science. We first propose related definitions to characterize CogSec and review the literature history. We further investigate the key research challenges and techniques of CogSec, including human-content cognition mechanism, social influence and opinion diffusion, fake news detection and malicious bot detection. Finally, we summarize the open issues and future research directions, such as early detection of fake news, explainable fake news debunking, social contagion and diffusion models of fake news, and so on.

Includes members:
  Member "the role of user profile for fake news detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "discovering differential features adversarial learning for information credibility evaluation")
  Member "influence of fake news in twitter during the 2016 us presidential election":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "topology comparison of twitter diffusion networks effectively reveals misleading information")
  Member "studying fake news via network analysis detection and mitigation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mining disinformation and fake news concepts methods and recent advancements")
  Member "techniques for interpretable machine learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "causal interpretability for machine learning problems methods and evaluation")
  Member "declare debunking fake news and false claims using evidence aware deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mining disinformation and fake news concepts methods and recent advancements")
  Member "fake news a survey of research detection methods and opportunities":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mining disinformation and fake news concepts methods and recent advancements")
  Member "opinion dynamics with varying susceptibility to persuasion":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "network disruption maximizing disagreement and polarization in social networks")
  Member "deepinf social influence prediction with deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "cross gcn enhancing graph convolutional network with k order feature interactions")

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.CY(Computers and Society)