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 "a survey of signed network mining in social media"):
  Abstract: Many real-world relations can be represented by signed networks with positive and negative links, as a result of which signed network analysis has attracted increasing attention from multiple disciplines. With the increasing prevalence of social media networks, signed network analysis has evolved from developing and measuring theories to mining tasks. In this article, we present a review of mining signed networks in the context of social media and discuss some promising research directions and new frontiers. We begin by giving basic concepts and unique properties and principles of signed networks. Then we classify and review tasks of signed network mining with representative algorithms. We also delineate some tasks that have not been extensively studied with formal definitions and also propose research directions to expand the field of signed network mining.

Includes members:
  Member "signed link analysis in social media networks":
    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 "stochastic block model and exploratory analysis in signed networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a block based generative model for attributed networks embedding")
  Member "signed graph embedding when everybody can sit closer to friends than enemies":
    also connected through other hyperedges:
      (none)
  Member "overlapping community detection in networks with positive and negative links":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on equivalence of likelihood maximization of stochastic block model and constrained nonnegative matrix factorization")
  Member "negative link prediction in social media":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "social science guided feature engineering a novel approach to signed link analysis")
  Member "applications of structural balance in signed social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "signed network structural analysis and applications with a focus on balance theory")
  Member "breaking the small cluster barrier of graph clustering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "searching for a single community in a graph")
  Member "prediction and clustering in signed networks a local to global perspective":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sne signed network embedding")

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)