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 "the complexity of probabilistic lobbying"):
  Abstract: We propose models for lobbying in a probabilistic environment, in which an actor (called "The Lobby") seeks to influence voters' preferences of voting for or against multiple issues when the voters' preferences are represented in terms of probabilities. In particular, we provide two evaluation criteria and two bribery methods to formally describe these models, and we consider the resulting forms of lobbying with and without issue weighting. We provide a formal analysis for these problems of lobbying in a stochastic environment, and determine their classical and parameterized complexity depending on the given bribery/evaluation criteria and on various natural parameterizations. Specifically, we show that some of these problems can be solved in polynomial time, some are NP-complete but fixed-parameter tractable, and some are W[2]-complete. Finally, we provide approximability and inapproximability results for these problems and several variants.

Includes members:
  Member "manipulation of nanson s and baldwin s rules":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "detecting possible manipulators in elections")
  Member "complexity of and algorithms for borda manipulation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the complexity of possible winners on partial chains")
  Member "parameterizing by the number of numbers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "combinatorial n fold integer programming and applications")
  Member "control complexity in fallback voting":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a parameterized perspective on protecting elections")
  Member "the shield that never was societies with single peaked preferences are more open to manipulation and control":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the complexity of constructive control under nearly single peaked preferences")
  Member "sincere strategy preference based approval voting fully resists constructive control and broadly resists destructive control":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a parameterized perspective on protecting elections")
  Member "satzilla portfolio based algorithm selection for sat":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deciding the consistency of non linear real arithmetic constraints with a conflict driven search using cylindrical algebraic coverings")
  Member "llull and copeland voting computationally resist bribery and control":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "achieving fully proportional representation is easy in practice")

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.CC(Computational Complexity)