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 "balance and frustration in signed networks"):
  Abstract: The frustration index is a key measure for analysing signed networks, which has been underused due to its computational complexity. We use an exact optimisation-based method to analyse frustration as a global structural property of signed networks coming from diverse application areas. In the classic friend-enemy interpretation of balance theory, a by-product of computing the frustration index is the partitioning of nodes into two internally solidary but mutually hostile groups. #R##N#The main purpose of this paper is to present general methodology for answering questions related to partial balance in signed networks, and apply it to a range of representative examples that are now analysable because of advances in computational methods. #R##N#We provide exact numerical results on social and biological signed networks, networks of formal alliances and antagonisms between countries, and financial portfolio networks. Molecular graphs of carbon and Ising models are also considered. We point out several mistakes in the signed networks literature caused by inaccurate computation, implementation errors or inappropriate measures.

Includes members:
  Member "measuring partial balance in signed networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "detecting coalitions by optimally partitioning signed networks of political collaboration")
  Member "computing the line index of balance using integer programming optimisation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "detecting coalitions by optimally partitioning signed networks of political collaboration")
  Member "evaluating balance on social networks from their simple cycles":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "signed network structural analysis and applications with a focus on balance theory")
  Member "a general purpose algorithm for counting simple cycles and simple paths of any length":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "signed network structural analysis and applications with a focus on balance theory")
  Member "an exact method for computing the frustration index in signed networks using binary programming":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "detecting coalitions by optimally partitioning signed networks of political collaboration")
  Member "applications of structural balance in signed social networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "signed network structural analysis and applications with a focus on balance theory")
  Member "correlation clustering with a fixed number of clusters":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "spectral clustering of signed graphs via matrix power means")

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)