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: "minority becomes majority in social networks"
  Abstract: It is often observed that agents tend to imitate the behavior of their neighbors in a social network. This imitating behavior might lead to the strategic decision of adopting a public behavior that differs from what the agent believes is the right one and this can subvert the behavior of the population as a whole. #R##N#In this paper, we consider the case in which agents express preferences over two alternatives and model social pressure with the majority dynamics: at each step an agent is selected and its preference is replaced by the majority of the preferences of her neighbors. In case of a tie, the agent does not change her current preference. A profile of the agents' preferences is stable if the preference of each agent coincides with the preference of at least half of the neighbors (thus, the system is in equilibrium). #R##N#We ask whether there are network topologies that are robust to social pressure. That is, we ask if there are graphs in which the majority of preferences in an initial profile always coincides with the majority of the preference in all stable profiles reachable from that profile. We completely characterize the graphs with this robustness property by showing that this is possible only if the graph has no edge or is a clique or very close to a clique. In other words, except for this handful of graphs, every graph admits at least one initial profile of preferences in which the majority dynamics can subvert the initial majority. We also show that deciding whether a graph admits a minority that becomes majority is NP-hard when the minority size is at most 1/4-th of the social network size.

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"
    - "controlling elections through social influence"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "maximizing the spread of cascades using network design"
    - "on budgeted influence maximization in social networks"

Connected through hyperedge HE-2 (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"
    - "controlling elections through social influence"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "complexity of shift bribery in committee elections"
    - "determining possible and necessary winners under common voting rules given partial orders"

Connected through hyperedge HE-3 (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"
    - "controlling elections through social influence"
    - "complexity of shift bribery in committee elections"
    - "influence maximization near optimal time complexity meets practical efficiency"
    - "anyone but him the complexity of precluding an alternative"

Connected through hyperedge HE-4 (induced by source paper "election control in social networks via edge addition or removal"):
  with members:
    - "election manipulation on social networks with messages on multiple candidates"
    - "exploiting social influence to control elections based on scoring rules"
    - "election control with voters uncertainty hardness and approximation results"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"

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

Connected through hyperedge HE-6 (induced by source paper "bounding the inefficiency of compromise in opinion formation"):
  with members:
    - "how bad is forming your own opinion"

Connected through hyperedge HE-7 (induced by source paper "discrete preference games in heterogeneous social networks subverted majorities and the swing player"):
  with members:
    - "on discrete preferences and coordination"
    - "how bad is forming your own opinion"

Connected through hyperedge HE-8 (induced by source paper "decentralized dynamics for finite opinion games"):
  with members:
    - "on discrete preferences and coordination"
    - "convergence to equilibrium of logit dynamics for strategic games"
    - "how bad is forming your own opinion"
    - "opinion dynamics in social networks a local interaction game with stubborn agents"
    - "metastability of logit dynamics for coordination games"
    - "mixing time and stationary expected social welfare of logit dynamics"

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)