human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "possible and necessary winner problem in social polls"
  Abstract: Social networks are increasingly being used to conduct polls. We introduce a simple model of such social polling. We suppose agents vote sequentially, but the order in which agents choose to vote is not necessarily fixed. We also suppose that an agent's vote is influenced by the votes of their friends who have already voted. Despite its simplicity, this model provides useful insights into a number of areas including social polling, sequential voting, and manipulation. We prove that the number of candidates and the network structure affect the computational complexity of computing which candidate necessarily or possibly can win in such a social poll. For social networks with bounded treewidth and a bounded number of candidates, we provide polynomial algorithms for both problems. In other cases, we prove that computing which candidates necessarily or possibly win are computationally intractable.

Connected through hyperedge HE-1 (induced by source paper "complexity of manipulation with partial information in voting"):
  with members:
    - "manipulative elicitation a new attack on elections with incomplete preferences"
    - "on the exact amount of missing information that makes finding possible winners hard"
    - "complexity of manipulation in elections with partial votes"
    - "frugal bribery in voting"
    - "detecting possible manipulators in elections"
    - "kernelization complexity of possible winner and coalitional manipulation problems in voting"
    - "the computational impact of partial votes on strategic voting"
    - "asymptotic collusion proofness of voting rules the case of large number of candidates"

Connected through hyperedge HE-2 (induced by source paper "manipulation is harder with incomplete votes"):
  with members:
    - "complexity of manipulation bribery and campaign management in bucklin and fallback voting"
    - "determining possible and necessary winners under common voting rules given partial orders"
    - "dominating manipulations in voting with partial information"
    - "an empirical study of the manipulability of single transferable voting"

Connected through hyperedge HE-3 (induced by source paper "myhill nerode methods for hypergraphs"):
  with members:
    - "approximating acyclicity parameters of sparse hypergraphs"
    - "matroid pathwidth and code trellis complexity"

Question: Please tell me which class the center node 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)