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: "the velocity of censorship high fidelity detection of microblog post deletions"
  Abstract: Weibo and other popular Chinese microblogging sites are well known for exercising internal censorship, to comply with Chinese government requirements. This research seeks to quantify the mechanisms of this censorship: how fast and how comprehensively posts are deleted.Our analysis considered 2.38 million posts gathered over roughly two months in 2012, with our attention focused on repeatedly visiting "sensitive" users. This gives us a view of censorship events within minutes of their occurrence, albeit at a cost of our data no longer representing a random sample of the general Weibo population. We also have a larger 470 million post sampling from Weibo's public timeline, taken over a longer time period, that is more representative of a random sample. #R##N#We found that deletions happen most heavily in the first hour after a post has been submitted. Focusing on original posts, not reposts/retweets, we observed that nearly 30% of the total deletion events occur within 5- 30 minutes. Nearly 90% of the deletions happen within the first 24 hours. Leveraging our data, we also considered a variety of hypotheses about the mechanisms used by Weibo for censorship, such as the extent to which Weibo's censors use retrospective keyword-based censorship, and how repost/retweet popularity interacts with censorship. We also used natural language processing techniques to analyze which topics were more likely to be censored.

Connected through hyperedge HE-1 (induced by source paper "linguistic fingerprints of internet censorship the case of sinaweibo"):
  with members:
    - "linguistic characteristics of censorable language on sinaweibo"
    - "defeating image obfuscation with deep learning"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-2 (induced by source paper "assessing post deletion in sina weibo multi modal classification of hot topics"):
  with members:
    - "linguistic characteristics of censorable language on sinaweibo"
    - "improved relation classification by deep recurrent neural networks with data augmentation"
    - "understanding data augmentation for classification when to warp"
    - "learning deep features for discriminative localization"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-3 (induced by source paper "deception strategies and threats for online discussions"):
  with members:
    - "influence of fake news in twitter during the 2016 us presidential election"
    - "anatomy of an online misinformation network"
    - "the spread of low credibility content by social bots"
    - "soc2seq social embedding meets conversation model"
    - "reuters tracer toward automated news production using large scale social media data"
    - "early detection of promoted campaigns on social media"
    - "discovery retrieval and analysis of star wars botnet in twitter"
    - "limited individual attention and online virality of low quality information"

Connected through hyperedge HE-4 (induced by source paper "linguistic characteristics of censorable language on sinaweibo"):
  with members:
    - "defeating image obfuscation with deep learning"
    - "efficient estimation of word representations in vector space"
    - "estimating continuous distributions in bayesian classifiers"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-5 (induced by source paper "censors delay in blocking circumvention proxies"):
  with members:
    - "dimming the internet detecting throttling as a mechanism of censorship in iran"

Connected through hyperedge HE-6 (induced by source paper "systemization of pluggable transports for censorship resistance"):
  with members:
    - "a framework for the game theoretic analysis of censorship resistance"
    - "games without frontiers investigating video games as a covert channel"
    - "on modeling the costs of censorship"
    - "dimming the internet detecting throttling as a mechanism of censorship in iran"
    - "scramblesuit a polymorph network protocol to circumvent censorship"
    - "sweet serving the web by exploiting email tunnels"
    - "using transcoding for hidden communication in ip telephony"

Connected through hyperedge HE-7 (induced by source paper "toward automatic censorship detection in microblogs"):
  with members:
    - "tracking and quantifying censorship on a chinese microblogging site"

Connected through hyperedge HE-8 (induced by source paper "large scale spatiotemporal characterization ofinconsistencies in the world s largest firewall"):
  with members:
    - "detecting intentional packet drops on the internet via tcp ip side channels extended version"

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)