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: "social networks with competing products"
  Abstract: We introduce a new threshold model of social networks, in which the nodes influenced by their neighbours can adopt one out of several alternatives. We characterize social networks for which adoption of a product by the whole network is possible (respectively necessary) and the ones for which a unique outcome is guaranteed. These characterizations directly yield polynomial time algorithms that allow us to determine whether a given social network satisfies one of the above properties. #R##N#We also study algorithmic questions for networks without unique outcomes. We show that the problem of determining whether a final network exists in which all nodes adopted some product is NP-complete. In turn, the problems of determining whether a given node adopts some (respectively, a given) product in some (respectively, all) network(s) are either co-NP complete or can be solved in polynomial time. #R##N#Further, we show that the problem of computing the minimum possible spread of a product is NP-hard to approximate with an approximation ratio better than $\Omega(n)$, in contrast to the maximum spread, which is efficiently computable. Finally, we clarify that some of the above problems can be solved in polynomial time when there are only two products.

Connected through hyperedge HE-1 (induced by source paper "on multi cascade influence maximization model hardness and algorithmic framework"):
  with members:
    - "on misinformation containment in online social networks"
    - "balancing information exposure in social networks"
    - "distributed rumor blocking with multiple positive cascades"
    - "an efficient randomized algorithm for rumor blocking in online social networks"
    - "almost polynomial ratio eth hardness of approximating densest k subgraph"
    - "stop and stare optimal sampling algorithms for viral marketing in billion scale networks"
    - "correlated cascades compete or cooperate"
    - "from competition to complementarity comparative influence diffusion and maximization"

Connected through hyperedge HE-2 (induced by source paper "convergence of opinion diffusion is pspace complete"):
  with members:
    - "pspace completeness of majority automata networks"
    - "paradoxes in social networks with multiple products"

Connected through hyperedge HE-3 (induced by source paper "a network based rating system and its resistance to bribery"):
  with members:
    - "social network games"
    - "how hard is bribery in elections"

Connected through hyperedge HE-4 (induced by source paper "marketing impact on diffusion in social networks"):
  with members:
    - "the budget constrained functional dependency"
    - "facebook and the epistemic logic of friendship"

Connected through hyperedge HE-5 (induced by source paper "knowledge in communication networks"):
  with members:
    - "epistemic logic for communication chains"

Connected through hyperedge HE-6 (induced by source paper "paradoxes in social networks with multiple products"):
  with members:
    - "graphical models for game theory"
    - "social network games with obligatory product selection"
    - "choosing products in social networks"
    - "on the hardness of network design for bottleneck routing games"
    - "social network games"
    - "diffusion in social networks with competing products"
    - "competitive contagion in networks"

Connected through hyperedge HE-7 (induced by source paper "social network games"):
  with members:
    - "graphical models for game theory"
    - "social network games with obligatory product selection"
    - "paradoxes in social networks with multiple products"
    - "choosing products in social networks"
    - "a classification of weakly acyclic games"
    - "diffusion in social networks with competing products"

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.SI(Social and Information Networks)