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 "privacy preserving social media data publishing"):
  Abstract: User-generated social media data are exploding and also of high demand in public and private sectors. The disclosure of complete and intact social media data exacerbates the threats to user privacy. In this paper, we first identify a text-based user-linkage attack on current social media data publishing practices, in which the real users of anonymous IDs in a published dataset can be pinpointed based on the users' unprotected text data. Then we propose a framework for differentially privacy-preserving social media data publishing for the first time in literature. Within our framework, social media data service providers can publish perturbed datasets to provide differential privacy to social media users while offering high data utility to social media data consumers. Our differential privacy mechanism is based on a novel notion of $\epsilon$-text indistinguishability, which we propose to thwart the text-based user-linkage attack. Extensive experiments on real-world and simulated datasets confirm that our framework can enable high-level differential privacy protection and also high data utility at the same time.

Includes members:
  Member "linkmirage how to anonymize links in dynamic social systems":
    also connected through other hyperedges:
      (none)
  Member "your actions tell where you are uncovering twitter users in a metropolitan area":
    also connected through other hyperedges:
      (none)
  Member "geo indistinguishability differential privacy for location based systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "local information privacy and its application to privacy preserving data aggregation")
  Member "calibrating data to sensitivity in private data analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "locally private hypothesis selection")
  Member "preserving link privacy in social network based systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "target privacy preserving for social networks")
  Member "a learning theory approach to non interactive database privacy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "pure differentially private summation from anonymous messages")
  Member "compressive mechanism utilizing sparse representation in differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "secure and efficient compressed sensing based encryption with sparse matrices")
  Member "differential privacy via wavelet transforms":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "differentially private m band wavelet based mechanisms in machine learning environments")

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.SI(Social and Information Networks)