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 "a quantitative approach to understanding online antisemitism"):
  Abstract: A new wave of growing antisemitism, driven by fringe Web communities, is an increasingly worrying presence in the socio-political realm. The ubiquitous and global nature of the Web has provided tools used by these groups to spread their ideology to the rest of the Internet. Although the study of antisemitism and hate is not new, the scale and rate of change of online data has impacted the efficacy of traditional approaches to measure and understand this worrying trend. In this paper, we present a large-scale, quantitative study of online antisemitism. We collect hundreds of million comments and images from alt-right Web communities like 4chan's Politically Incorrect board (/pol/) and the Twitter clone, Gab. Using scientifically grounded methods, we quantify the escalation and spread of antisemitic memes and rhetoric across the Web. We find the frequency of antisemitic content greatly increases (in some cases more than doubling) after major political events such as the 2016 US Presidential Election and the "Unite the Right" rally in Charlottesville. Furthermore, this antisemitism appears in tandem with sharp increases in white ethnic nationalist content on the same communities. We extract semantic embeddings from our corpus of posts and demonstrate how automated techniques can discover and categorize the use of antisemitic terminology. We additionally examine the prevalence and spread of the antisemitic "Happy Merchant" meme, and in particular how these fringe communities influence its propagation to more mainstream services like Twitter and Reddit. Taken together, our results provide a data-driven, quantitative framework for understanding online antisemitism. Our open and scientifically grounded methods serve as a framework to augment current qualitative efforts by anti-hate groups, providing new insights into the growth and spread of antisemitism online.

Includes members:
  Member "what is gab a bastion of free speech or an alt right echo chamber":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "from pick up artists to incels a data driven sketch of the manosphere")
  Member "a unified deep learning architecture for abuse detection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nlpr srpol at semeval 2019 task 6 and task 5 linguistically enhanced deep learning offensive sentence classifier")
  Member "automatic detection of online jihadist hate speech":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "facilitating on line opinion dynamics by mining expressions of causation the case of climate change debates on the guardian")
  Member "mobilizing the trump train understanding collective action in a political trolling community":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "understanding web archiving services and their mis use on social media":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the pushshift reddit dataset")
  Member "peer to peer hate hate speech instigators and their targets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a benchmark dataset for learning to intervene in online hate speech")
  Member "hate lingo a target based linguistic analysis of hate speech in social media":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a framework for the computational linguistic analysis of dehumanization")
  Member "on the origins of memes by means of fringe web communities":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "the pushshift reddit dataset")

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)