human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "different spirals of sameness a study of content sharing in mainstream and alternative media"
  Abstract: In this paper, we analyze content sharing between news sources in the alternative and mainstream media using a dataset of 713K articles and 194 sources. We find that content sharing happens in tightly formed communities, and these communities represent relatively homogeneous portions of the media landscape. Through a mix-method analysis, we find several primary content sharing behaviors. First, we find that the vast majority of shared articles are only shared with similar news sources (i.e. same community). Second, we find that despite these echo-chambers of sharing, specific sources, such as The Drudge Report, mix content from both mainstream and conspiracy communities. Third, we show that while these differing communities do not always share news articles, they do report on the same events, but often with competing and counter-narratives. Overall, we find that the news is homogeneous within communities and diverse in between, creating different spirals of sameness.

Connected through hyperedge HE-1 (induced by source paper "safe similarity aware multi modal fake news detection"):
  with members:
    - "fake news early detection a theory driven model"
    - "learning hierarchical discourse level structure for fake news detection"
    - "learning cross modal embeddings with adversarial networks for cooking recipes and food images"
    - "fakenewsnet a data repository with news content social context and dynamic information for studying fake news on social media"
    - "fake news a survey of research detection methods and opportunities"
    - "ti cnn convolutional neural networks for fake news detection"
    - "liar liar pants on fire a new benchmark dataset for fake news detection"
    - "show and tell lessons learned from the 2015 mscoco image captioning challenge"

Connected through hyperedge HE-2 (induced by source paper "trustworthy misinformation mitigation with soft information nudging"):
  with members:
    - "nela gt 2018 a large multi labelled news dataset for the study of misinformation in news articles"
    - "rating reliability and bias in news articles does ai assistance help everyone"
    - "auditing radicalization pathways on youtube"
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "predicting factuality of reporting and bias of news media sources"
    - "this just in fake news packs a lot in title uses simpler repetitive content in text body more similar to satire than real news"
    - "csi a hybrid deep model for fake news detection"
    - "node2vec scalable feature learning for networks"

Question: Please tell me which class the center node 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)