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 online manipulation of sequential elections"):
  Abstract: Most work on manipulation assumes that all preferences are known to the manipulators. However, in many settings elections are open and sequential, and manipulators may know the already cast votes but may not know the future votes. We introduce a framework, in which manipulators can see the past votes but not the future ones, to model online coalitional manipulation of sequential elections, and we show that in this setting manipulation can be extremely complex even for election systems with simple winner problems. Yet we also show that for some of the most important election systems such manipulation is simple in certain settings. This suggests that when using sequential voting, one should pay great attention to the details of the setting in choosing one's voting rule. Among the highlights of our classifications are: We show that, depending on the size of the manipulative coalition, the online manipulation problem can be complete for each level of the polynomial hierarchy or even for PSPACE. We obtain the most dramatic contrast to date between the nonunique-winner and unique-winner models: Online weighted manipulation for plurality is in P in the nonunique-winner model, yet is coNP-hard (constructive case) and NP-hard (destructive case) in the unique-winner model. And we obtain what to the best of our knowledge are the first P^NP[1]-completeness and P^NP-completeness results in the field of computational social choice, in particular proving such completeness for, respectively, the complexity of 3-candidate and 4-candidate (and unlimited-candidate) online weighted coalition manipulation of veto elections.

Includes members:
  Member "online voter control in sequential elections":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "computational social choice and computational complexity bffs")
  Member "an atypical survey of typical case heuristic algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "discovering archipelagos of tractability for constraint satisfaction and counting")
  Member "new candidates welcome possible winners with respect to the addition of new candidates":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the complexity of online bribery in sequential elections extended abstract")
  Member "determining possible and necessary winners under common voting rules given partial orders":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the complexity of possible winners on partial chains")
  Member "taking the final step to a full dichotomy of the possible winner problem in pure scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the complexity of possible winners on partial chains")
  Member "towards a dichotomy for the possible winner problem in elections based on scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the complexity of possible winners on partial chains")
  Member "equilibria of plurality voting with abstentions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sybil resilient social choice with partial participation")
  Member "towards a dichotomy of finding possible winners in elections based on scoring rules":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "complexity of manipulation with partial information in voting")

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)