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: "meme creation and sharing processes individuals shaping the masses"
  Abstract: The propagation of online memes is initially influenced by meme creators and secondarily by meme consumers, whose individual sharing decisions accumulate to determine total meme propagation. We characterize this as a sender/receiver sequence in which the first sender is also the creator. This sequence consists of two distinct processes, the creation process and the sharing process. We investigated these processes separately to determine their individual influence on sharing outcomes. Our study observed participants creating memes in the lab. We then tracked the sharing of those memes, derived a model of sharing behavior, and implemented our sharing model in a contagion simulation. #R##N#Although we assume meme consumers typically have little or no information about a meme's creator when making a decision about whether to share a meme (and vice versa), we nevertheless ask whether consumer re-sharing behavior can be predicted based on features of the creator. Using human participants, web log monitoring, and statistical model fitting, the resulting Creator Model of Re-sharing Behavior predicts 11.5% of the variance in the behavior of consumers. Even when we know nothing about re-sharers of a meme, we can predict something about their behavior by observing the creation process. #R##N#To investigate the individual re-sharing decisions that, together, constitute a meme's total consumer response, we built a statistical model from human observation. Receivers make their decision to share as a function of the meme's content and their reaction to it, which we model as a consumer's decision to share. The resulting Consumer Model of Sharing Decisions describes 37.5% of the variance in this decision making process.

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)