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 "tell me something my friends do not know diversity maximization in social networks"):
  Abstract: Social media have a great potential to improve information dissemination in our society, yet, they have been held accountable for a number of undesirable effects, such as polarization and filter bubbles. It is thus important to understand these negative phenomena and develop methods to combat them. In this paper we propose a novel approach to address the problem of breaking filter bubbles in social media. We do so by aiming to maximize the diversity of the information exposed to connected social-media users. We formulate the problem of maximizing the diversity of exposure as a quadratic-knapsack problem. We show that the proposed diversity-maximization problem is inapproximable, and thus, we resort to polynomial non-approximable algorithms, inspired by solutions developed for the quadratic-knapsack problem, as well as scalable greedy heuristics. We complement our algorithms with instance-specific upper bounds, which are used to provide empirical approximation guarantees for the given problem instances. Our experimental evaluation shows that a proposed greedy algorithm followed by randomized local search is the algorithm of choice given its quality-vs.-efficiency trade-off.

Includes members:
  Member "minimizing polarization and disagreement in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "choice set optimization under discrete choice models of group decisions")
  Member "balancing information exposure in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "combating fake news a survey on identification and mitigation techniques")
  Member "joint non negative matrix factorization for learning ideological leaning on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "users polarization on facebook and youtube":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "tubes bubbles topological confinement of youtube recommendations")
  Member "reducing controversy by connecting opposing views":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "quantifying controversy in social media":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "language in our time an empirical analysis of hashtags")

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)