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: "career transitions and trajectories a case study in computing"
  Abstract: From artificial intelligence to network security to hardware design, it is well-known that computing research drives many important technological and societal advancements. However, less is known about the long-term career paths of the people behind these innovations. What do their careers reveal about the evolution of computing research? Which institutions were and are the most important in this field, and for what reasons? Can insights into computing career trajectories help predict employer retention?   In this paper we analyze several decades of post-PhD computing careers using a large new dataset rich with professional information, and propose a versatile career network model, R 3 , that captures temporal career dynamics. With R 3 we track important organizations in computing research history, analyze career movement between industry, academia, and government, and build a powerful predictive model for individual career transitions. Our study, the first of its kind, is a starting point for understanding computing research careers, and may inform employer recruitment and retention mechanisms at a time when the demand for specialized computational expertise far exceeds supply.

Connected through hyperedge HE-1 (induced by source paper "discovering archetypes to interpret evolution of individual behavior"):
  with members:
    - "can we count on social media metrics first insights into the active scholarly use of social media"
    - "the misleading narrative of the canonical faculty productivity trajectory"
    - "gender productivity and prestige in computer science faculty hiring networks"
    - "the mythos of model interpretability"
    - "why should i trust you explaining the predictions of any classifier"
    - "from amateurs to connoisseurs modeling the evolution of user expertise through online reviews"
    - "clustering hidden markov models with variational hem"
    - "analysis of computer science communities based on dblp"

Connected through hyperedge HE-2 (induced by source paper "automated discovery and classification of training videos for career progression"):
  with members:
    - "on analyzing job hop behavior and talent flow networks"
    - "distributed representations of sentences and documents"

Connected through hyperedge HE-3 (induced by source paper "hubs and authorities of the scientific migration network"):
  with members:
    - "a machine learning approach to modeling human migration"
    - "global multi layer network of human mobility"

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)