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 "beyond content analysis detecting targeted ads via distributed counting"):
  Abstract: Being able to check whether an online advertisement has been targeted is essential for resolving privacy controversies and implementing in practice data protection regulations like GDPR, CCPA, and COPPA. In this paper we describe the design, implementation, and deployment of an advertisement auditing system called iWnder that uses crowdsourcing to reveal in real time whether a display advertisement has been targeted or not. Crowdsourcing simplifies the detection of targeted advertising, but requires reporting to a central repository the impressions seen by different users, thereby jeopardising their privacy. We break this deadlock with a privacy preserving data sharing protocol that allows iWnder to compute global statistics required to detect targeting, while keeping the advertisements seen by individual users and their browsing history private. We conduct a simulation study to explore the effect of different parameters and a live validation to demonstrate the accuracy of our approach. Unlike previous solutions, iWnder can even detect indirect targeting, i.e., marketing campaigns that promote a product or service whose description bears no semantic overlap with its targeted audience.

Includes members:
  Member "on microtargeting socially divisive ads a case study of russia linked ad campaigns on facebook":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "can whatsapp counter misinformation by limiting message forwarding")
  Member "tracing information flows between ad exchanges using retargeted ads":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stop tracking me bro differential tracking of user demographics on hyper partisan websites")
  Member "myadchoices bringing transparency and control to online advertising":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "discrimination through optimization how facebook s ad delivery can lead to biased outcomes")
  Member "building a rappor with the unknown privacy preserving learning of associations and data dictionaries":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "wireless federated learning with local differential privacy")
  Member "efficient private statistics with succinct sketches":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "pure differentially private summation from anonymous messages")
  Member "i always feel like somebody s watching me measuring online behavioural advertising":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "stop tracking me bro differential tracking of user demographics on hyper partisan websites")
  Member "adscape harvesting and analyzing online display ads":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "measuring abuse in web push advertising")
  Member "automated experiments on ad privacy settings a tale of opacity choice and discrimination":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "artificial intelligent ethics in the digital era an engineering ethical framework proposal")

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)