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: "auditing radicalization pathways on youtube"
  Abstract: Non-profits, as well as the media, have hypothesized the existence of a radicalization pipeline on YouTube, claiming that users systematically progress towards more extreme content on the platform. Yet, there is to date no substantial quantitative evidence of this alleged pipeline. To close this gap, we conduct a large-scale audit of user radicalization on YouTube. We analyze 330,925 videos posted on 349 channels, which we broadly classified into four types: Media, the Alt-lite, the Intellectual Dark Web (I.D.W.), and the Alt-right. According to the aforementioned radicalization hypothesis, channels in the I.D.W. and the Alt-lite serve as gateways to fringe far-right ideology, here represented by Alt-right channels. Processing 72M+ comments, we show that the three channel types indeed increasingly share the same user base; that users consistently migrate from milder to more extreme content; and that a large percentage of users who consume Alt-right content now consumed Alt-lite and I.D.W. content in the past. We also probe YouTube's recommendation algorithm, looking at more than 2M video and channel recommendations between May/July 2019. We find that Alt-lite content is easily reachable from I.D.W. channels, while Alt-right videos are reachable only through channel recommendations. Overall, we paint a comprehensive picture of user radicalization on YouTube.

Connected through hyperedge HE-1 (induced by source paper "understanding the incel community on youtube"):
  with members:
    - "disturbed youtube for kids characterizing and detecting inappropriate videos targeting young children"
    - "a quantitative approach to understanding online antisemitism"
    - "you know what to do proactive detection of youtube videos targeted by coordinated hate attacks"
    - "analyzing right wing youtube channels hate violence and discrimination"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-2 (induced by source paper "the problem with metrics is a fundamental problem for ai"):
  with members:
    - "dark patterns at scale findings from a crawl of 11k shopping websites"
    - "model cards for model reporting"
    - "datasheets for datasets"

Connected through hyperedge HE-3 (induced by source paper "the engagement diversity connection evidence from a field experiment on spotify"):
  with members:
    - "diversity and inclusion metrics for subset selection"

Connected through hyperedge HE-4 (induced by source paper "temporal effects of unmoderated hate speech in gab"):
  with members:
    - "what is gab a bastion of free speech or an alt right echo chamber"
    - "all you need is love evading hate speech detection"
    - "challenges in discriminating profanity from hate speech"
    - "the effect of extremist violence on hateful speech online"
    - "hate speech dataset from a white supremacy forum"
    - "thou shalt not hate countering online hate speech"
    - "spread of hate speech in online social media"
    - "large scale crowdsourcing and characterization of twitter abusive behavior"

Connected through hyperedge HE-5 (induced by source paper "online disinformation and the role of wikipedia"):
  with members:
    - "citation needed a taxonomy and algorithmic assessment of wikipedia s verifiability"
    - "the wisdom of polarized crowds"
    - "the fact extraction and verification fever shared task"
    - "exposing deepfake videos by detecting face warping artifacts"
    - "fake news a survey of research detection methods and opportunities"
    - "fever a large scale dataset for fact extraction and verification"
    - "strategies and influence of social bots in a 2017 german state election a case study on twitter"
    - "do social bots dream of electric sheep a categorisation of social media bot accounts"

Connected through hyperedge HE-6 (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"
    - "different spirals of sameness a study of content sharing in mainstream and alternative media"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "algorithmic extremism examining youtube s rabbit hole of radicalization"):
  with members:
    - "analyzing right wing youtube channels hate violence and discrimination"
    - "spider and the flies focused crawling on tumblr to detect hate promoting communities"
    - "sentiment analysis on youtube a brief survey"
    - "force directed graph drawing using social gravity and scaling"

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)