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 "how hard is bribery in elections"):
  Abstract: We study the complexity of influencing elections through bribery: How computationally complex is it for an external actor to determine whether by a certain amount of bribing voters a specified candidate can be made the election's winner? We study this problem for election systems as varied as scoring protocols and Dodgson voting, and in a variety of settings regarding homogeneous-vs.-nonhomogeneous electorate bribability, bounded-size-vs.-arbitrary-sized candidate sets, weighted-vs.-unweighted voters, and succinct-vs.-nonsuccinct input specification. We obtain both polynomial-time bribery algorithms and proofs of the intractability of bribery, and indeed our results show that the complexity of bribery is extremely sensitive to the setting. For example, we find settings in which bribery is NP-complete but manipulation (by voters) is in P, and we find settings in which bribing weighted voters is NP-complete but bribing voters with individual bribe thresholds is in P. For the broad class of elections (including plurality, Borda, k-approval, and veto) known as scoring protocols, we prove a dichotomy result for bribery of weighted voters: We find a simple-to-evaluate condition that classifies every case as either NP-complete or in P.

Includes members:
  Member "sincere strategy preference based approval voting fully resists constructive control and broadly resists destructive control":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a parameterized perspective on protecting elections")
  Member "on approximating optimal weighted lobbying and frequency of correctness versus average case polynomial time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the complexity of probabilistic lobbying")
  Member "copeland voting fully resists constructive control":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a parameterized perspective on protecting elections")
  Member "hybrid elections broaden complexity theoretic resistance to control":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a parameterized perspective on protecting elections")
  Member "a richer understanding of the complexity of election systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "computational social choice and computational complexity bffs")
  Member "dichotomy for voting systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the complexity of online bribery in sequential elections")
  Member "anyone but him the complexity of precluding an alternative":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "selecting voting locations for fun and profit")
  Member "guarantees for the success frequency of an algorithm for finding dodgson election winners":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "achieving fully proportional representation approximability results")

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.GT(Computer Science and Game Theory)