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: "controlling elections through social influence"
  Abstract: Election control considers the problem of an adversary who attempts to tamper with a voting process, in order to either ensure that their favored candidate wins (constructive control) or another candidate loses (destructive control). As online social networks have become significant sources of information for potential voters, a new tool in an attacker's arsenal is to effect control by harnessing social influence, for example, by spreading fake news and other forms of misinformation through online social media. #R##N#We consider the computational problem of election control via social influence, studying the conditions under which finding good adversarial strategies is computationally feasible. We consider two objectives for the adversary in both the constructive and destructive control settings: probability and margin of victory (POV and MOV, respectively). We present several strong negative results, showing, for example, that the problem of maximizing POV is inapproximable for any constant factor. On the other hand, we present approximation algorithms which provide somewhat weaker approximation guarantees, such as bicriteria approximations for the POV objective and constant-factor approximations for MOV. Finally, we present mixed integer programming formulations for these problems. Experimental results show that our approximation algorithms often find near-optimal control strategies, indicating that election control through social influence is a salient threat to election integrity.

Connected through hyperedge HE-1 (induced by source paper "election manipulation on social networks seeding edge removal edge addition"):
  with members:
    - "election control in social networks via edge addition or removal"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "minority becomes majority in social networks"
    - "maximizing the spread of cascades using network design"
    - "on budgeted influence maximization in social networks"

Connected through hyperedge HE-2 (induced by source paper "persuading voters it s easy to whisper it s hard to speak loud"):
  with members:
    - "on the tractability of public persuasion with no externalities"
    - "defending elections against malicious spread of misinformation"
    - "algorithmic persuasion with no externalities"
    - "computational aspects of private bayesian persuasion"
    - "algorithmic bayesian persuasion"
    - "hardness results for signaling in bayesian zero sum and network routing games"
    - "honest signaling in zero sum games is hard and lying is even harder"
    - "elections with few voters candidate control can be easy"

Connected through hyperedge HE-3 (induced by source paper "election control with voters uncertainty hardness and approximation results"):
  with members:
    - "vote for me election control via social influence in arbitrary scoring rule voting systems"
    - "election campaigning on social media politicians audiences and the mediation of political communication on facebook and twitter"
    - "election with bribed voter uncertainty hardness and approximation algorithm"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "complexity of shift bribery in committee elections"
    - "minority becomes majority in social networks"
    - "determining possible and necessary winners under common voting rules given partial orders"

Connected through hyperedge HE-4 (induced by source paper "exploiting social influence to control elections based on scoring rules"):
  with members:
    - "defending elections against malicious spread of misinformation"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "complexity of shift bribery in committee elections"
    - "influence maximization near optimal time complexity meets practical efficiency"
    - "minority becomes majority in social networks"
    - "anyone but him the complexity of precluding an alternative"

Connected through hyperedge HE-5 (induced by source paper "election manipulation on social networks with messages on multiple candidates"):
  with members:
    - "minority becomes majority in social networks"
    - "on budgeted influence maximization in social networks"

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.MA(Multiagent Systems)