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: "multi stage complex contagions"
  Abstract: The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide crucial insights into social influence and behavior-adoption cascades on networks. In this paper, we introduce a model of a multi-stage complex contagion on networks. Agents at different stages—which could, for example, represent differing levels of support for a social movement or differing levels of commitment to a certain product or idea—exert different amounts of influence on their neighbors. We demonstrate that the presence of even one additional stage introduces novel dynamical behavior, including interplay between multiple cascades, which cannot occur in single-stage contagion models. We find that cascades—and hence collective action—can be driven not only by high-stage influencers but also by low-stage influencers.

Connected through hyperedge HE-1 (induced by source paper "computational human dynamics"):
  with members:
    - "joint embedding of structure and features via graph convolutional networks"
    - "location occupation and semantics based socioeconomic status inference on twitter"
    - "the temporal event graph"
    - "link transmission centrality in large scale social networks"
    - "socioeconomic dependencies of linguistic patterns in twitter a multivariate analysis"
    - "graph embedding techniques applications and performance a survey"
    - "correlations and dynamics of consumption patterns in social economic networks"
    - "stream graphs and link streams for the modeling of interactions over time"

Connected through hyperedge HE-2 (induced by source paper "nonlinearity networks a 2020 vision"):
  with members:
    - "models of continuous time networks with tie decay diffusion and convection"
    - "tunable eigenvector based centralities for multiplex and temporal networks"
    - "architecture and evolution of semantic networks in mathematics texts"
    - "supracentrality analysis of temporal networks with directed interlayer coupling"
    - "using persistent homology to quantify a diurnal cycle in hurricane felix"
    - "persistent homology of geospatial data a case study with voting"
    - "network structure from rich but noisy data"
    - "random walks on simplicial complexes and the normalized hodge 1 laplacian"

Connected through hyperedge HE-3 (induced by source paper "complex contagions a decade in review"):
  with members:
    - "bots as virtual confederates design and ethics"
    - "virality prediction and community structure in social networks"
    - "the role of social networks in information diffusion"
    - "social influence in social advertising evidence from field experiments"
    - "modeling the adoption of innovations in the presence of geographic and media influences"
    - "are friends overrated a study for the social news aggregator digg com"

Connected through hyperedge HE-4 (induced by source paper "analysis of contagion maps on a class of networks that are spatially embedded in a torus"):
  with members:
    - "geometry helps to compare persistence diagrams"
    - "complex contagions in kleinberg s small world model"
    - "sustaining the internet with hyperbolic mapping"

Connected through hyperedge HE-5 (induced by source paper "the role of network analysis in industrial and applied mathematics a physical applied mathematics perspective"):
  with members:
    - "a framework for the construction of generative models for mesoscale structure in multilayer networks"
    - "generative benchmark models for mesoscale structures in multilayer networks"
    - "do cascades recur"
    - "pagerank beyond the web"
    - "modeling complex systems with adaptive networks"

Connected through hyperedge HE-6 (induced by source paper "the role of network analysis in industrial and applied mathematics"):
  with members:
    - "generative benchmark models for mesoscale structures in multilayer networks"
    - "do cascades recur"
    - "modeling complex systems with adaptive 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.SI(Social and Information Networks)