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: "occam s razor in opinion dynamics the weighted median influence process"
  Abstract: Nowadays public opinion formation is deeply influenced by social networks and faces unprecedented challenges such as opinion radicalization, echo chambers, and ideologization of public debates. Mathematical modeling of opinion dynamics plays a fundamental role in understanding the microscopic mechanisms of social interactions behind these macroscopic phenomena. The weighted-averaging opinion update is arguably the most widely adopted microscopic mechanism for opinion dynamics. However, such models based on weighted averaging are restricted in their predictive power and limited to stylized continuous opinion spectra. Here we point out that these models' limitation in predictability is not due to the lack of complexity, but because the weighted-averaging mechanism itself features a non-negligible unrealistic implication. By resolving this unrealistic feature in the framework of cognitive dissonance theory, we propose a novel opinion dynamics model based on a weighted-median mechanism instead. Surprisingly, such an inconspicuous change in microscopic mechanism leads to dramatic macroscopic consequences. In the spirit of Occam's razor, our new model, despite its simplicity in form, exhibits a sophisticated consensus-disagreement phase transition depending on the influence network structure. Our model gives perhaps the simplest answers to various open problems in sociology and political science, such as the connection between social marginalization and opinion radicalization, the mechanism for echo chambers, and the formation of multipolar opinion distributions. Remarkably, the weighted-median opinion dynamics are the first model applicable to ordered multiple-choice issues, which are prevalent in modern-day public debates and elections.

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)