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 "sampling the news producers a large news and feature data set for the study of the complex media landscape"):
  Abstract: The complexity and diversity of today's media landscape provides many challenges for researchers studying news producers. These producers use many different strategies to get their message believed by readers through the writing styles they employ, by repetition across different media sources with or without attribution, as well as other mechanisms that are yet to be studied deeply. To better facilitate systematic studies in this area, we present a large political news data set, containing over 136K news articles, from 92 news sources, collected over 7 months of 2017. These news sources are carefully chosen to include well-established and mainstream sources, maliciously fake sources, satire sources, and hyper-partisan political blogs. In addition to each article we compute 130 content-based and social media engagement features drawn from a wide range of literature on political bias, persuasion, and misinformation. With the release of the data set, we also provide the source code for feature computation. In this paper, we discuss the first release of the data set and demonstrate 4 use cases of the data and features: news characterization, engagement characterization, news attribution and content copying, and discovering news narratives.

Includes members:
  Member "liar liar pants on fire a new benchmark dataset for fake news detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "identifying the social signals that drive online discussions a case study of reddit communities":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "detecting toxicity in news articles application to bulgarian")
  Member "acquiring background knowledge to improve moral value prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "predicting demographics moral foundations and human values from digital behaviours")
  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-4 (induced by source paper "a feature driven approach for identifying pathogenic social media accounts")
  Member "a stylometric inquiry into hyperpartisan and fake news":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hgat hierarchical graph attention network for fake news detection")
  Member "automatically identifying fake news in popular twitter threads":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "exploring the ideological nature of journalists social networks on twitter and associations with news story content":
    also connected through other hyperedges:
      (none)
  Member "hoaxy a platform for tracking online misinformation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "topology comparison of twitter diffusion networks effectively reveals misleading information")

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)