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 "network disruption maximizing disagreement and polarization in social networks"):
  Abstract: Recent years have seen a marked increase in the spread of misinformation, a phenomenon which has been accelerated and amplified by social media such as Facebook and Twitter. While some actors spread misinformation to push a specific agenda, it has also been widely documented that others aim to simply disrupt the network by increasing disagreement and polarization across the network and thereby destabilizing society. Popular social networks are also vulnerable to large-scale attacks. Motivated by this reality, we introduce a simple model of network disruption where an adversary can take over a limited number of user profiles in a social network with the aim of maximizing disagreement and/or polarization in the network. #R##N#We investigate this model both theoretically and empirically. We show that the adversary will always change the opinion of a taken-over profile to an extreme in order to maximize disruption. We also prove that an adversary can increase disagreement / polarization at most linearly in the number of user profiles it takes over. Furthermore, we present a detailed empirical study of several natural algorithms for the adversary on both synthetic networks and real world (Reddit and Twitter) data sets. These show that even simple, unsophisticated heuristics, such as targeting centrists, can disrupt a network effectively, causing a large increase in disagreement / polarization. Studying the problem of network disruption through the lens of an adversary thus highlights the seriousness of the problem.

Includes members:
  Member "adversarial perturbations of opinion dynamics in networks":
    also connected through other hyperedges:
      (none)
  Member "analysis of strategy and spread of russia sponsored content in the us in 2017":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "beyond trolling malware induced misperception attacks on polarized facebook discourse")
  Member "opinion dynamics with varying susceptibility to persuasion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the mass fake news and cognition security")
  Member "minimizing polarization and disagreement in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "choice set optimization under discrete choice models of group decisions")
  Member "some like it hoax automated fake news detection in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "detecting fake news with capsule neural networks")
  Member "opinion maximization in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "angry birds flock together aggression propagation on social media")

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)