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 "systems applications of social networks"):
  Abstract: The aim of this article is to provide an understanding of social networks as a useful addition to the standard toolbox of techniques used by system designers. To this end, we give examples of how data about social links have been collected and used in different application contexts. We develop a broad taxonomy-based overview of common properties of social networks, review how they might be used in different applications, and point out potential pitfalls where appropriate. We propose a framework, distinguishing between two main types of social network-based user selection—personalised user selection, which identifies target users who may be relevant for a given source node, using the social network around the source as a context, and generic user selection or group delimitation, which filters for a set of users who satisfy a set of application requirements based on their social properties. Using this framework, we survey applications of social networks in three typical kinds of application scenarios: recommender systems, content-sharing systems (e.g., P2P or video streaming), and systems that defend against users who abuse the system (e.g., spam or sybil attacks). In each case, we discuss potential directions for future research that involve using social network properties.

Includes members:
  Member "a survey of signed network mining in social media":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "social science guided feature engineering a novel approach to signed link analysis")
  Member "the architecture of innovation tracking face to face interactions with ubicomp technologies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an open source sensor platform for analysis of group dynamics")
  Member "social bootstrapping how pinterest and last fm social communities benefit by borrowing links from facebook":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "providing a link prediction model based on structural and homophily similarity in social networks")
  Member "geo spotting mining online location based services for optimal retail store placement":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "under the hood of membership inference attacks on aggregate location time series")
  Member "social turing tests crowdsourcing sybil detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "uncovering coordinated networks on social media")
  Member "explore what if scenarios with song social network write generator":
    also connected through other hyperedges:
      (none)
  Member "uncovering social network sybils in the wild":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fawkes protecting personal privacy against unauthorized deep learning models")
  Member "empirical comparison of algorithms for network community detection":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "certified robustness of community detection against adversarial structural perturbation via randomized smoothing")

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)