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: "a longitudinal measurement study of 4chan s politically incorrect forum and its effect on the web"
  Abstract: Although it has been a part of the dark underbelly of the Internet since its inception, recent events have brought the discussion board site 4chan to the forefront of the world's collective mind. In particular, /pol/, 4chan's "Politically Incorrect" board has become a central figure in the outlandish 2016 Presidential election. Even though 4chan has long been viewed as the "final boss of the Internet," it remains relatively unstudied in the academic literature. #R##N#In this paper we analyze /pol/ along several axes using a dataset of over 8M posts. We first perform a general characterization that reveals how active posters are, as well as how some unique features of 4chan affect the flow of discussion. We then analyze the content posted to /pol/ with a focus on determining topics of interest and types of media shared, as well as the usage of hate speech and differences in poster demographics. We additionally provide quantitative evidence of /pol/'s collective attacks on other social media platforms. We perform a quantitative case study of /pol/'s attempt to poison anti-trolling machine learning technology by altering the language of hate on social media. Then, via analysis of comments from the 10s of thousands of YouTube videos linked on /pol/, we provide a mechanism for detecting attacks from /pol/ threads on 3rd party social media services.

Connected through hyperedge HE-1 (induced by source paper "detecting cyberbullying and cyberaggression in social media"):
  with members:
    - "mean birds detecting aggression and bullying on twitter"
    - "measuring gamergate a tale of hate sexism and bullying"
    - "poised spotting twitter spam off the beaten paths"
    - "hate is not binary studying abusive behavior of gamergate on twitter"
    - "kek cucks and god emperor trump a measurement study of 4chan s politically incorrect forum and its effects on the web"
    - "deep residual learning for image recognition"
    - "exploring cyberbullying and other toxic behavior in team competition online games"
    - "deep learning and the information bottleneck principle"

Connected through hyperedge HE-2 (induced by source paper "understanding abuse a typology of abusive language detection subtasks"):
  with members:
    - "automated hate speech detection and the problem of offensive language"
    - "deep learning for hate speech detection in tweets"
    - "detecting the hate code on social media"
    - "ex machina personal attacks seen at scale"
    - "measuring the reliability of hate speech annotations the case of the european refugee crisis"

Connected through hyperedge HE-3 (induced by source paper "measuring gamergate a tale of hate sexism and bullying"):
  with members:
    - "mean birds detecting aggression and bullying on twitter"
    - "kek cucks and god emperor trump a measurement study of 4chan s politically incorrect forum and its effects on the web"
    - "the social world of content abusers in community question answering"
    - "towards understanding cyberbullying behavior in a semi anonymous social network"

Connected through hyperedge HE-4 (induced by source paper "what s in a name understanding profile name reuse on twitter"):
  with members:
    - "kek cucks and god emperor trump a measurement study of 4chan s politically incorrect forum and its effects on the web"
    - "paying for likes understanding facebook like fraud using honeypots"
    - "i to me an anatomy of username changing behavior on twitter"

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.SI(Social and Information Networks)