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: "experiments on crowdsourcing policy assessment"
  Abstract: Can Crowds serve as useful allies in policy design? How do non-expert Crowds perform relative to experts in the assessment of policy measures? Does the geographic location of non-expert Crowds, with relevance to the policy context, alter the performance of non-experts Crowds in the assessment of policy measures? In this work, we investigate these questions by undertaking experiments designed to replicate expert policy assessments with non-expert Crowds recruited from Virtual Labor Markets. We use a set of ninety-six climate change adaptation policy measures previously evaluated by experts in the Netherlands as our control condition to conduct experiments using two discrete sets of non-expert Crowds recruited from Virtual Labor Markets. We vary the composition of our non-expert Crowds along two conditions: participants recruited from a geographical location directly relevant to the policy context and participants recruited at-large. We discuss our research methods in detail and provide the findings of our experiments.

Connected through hyperedge HE-1 (induced by source paper "the fundamentals of policy crowdsourcing"):
  with members:
    - "the contours of crowd capability"
    - "how to work a crowd developing crowd capital through crowdsourcing"
    - "crowdsourcing the policy cycle"
    - "a computational model of crowds for collective intelligence"
    - "crowdsourcing for participatory democracies efficient elicitation of social choice functions"
    - "government and social media a case study of 31 informational world cities"
    - "the theory of crowd capital"
    - "the labor economics of paid crowdsourcing"

Connected through hyperedge HE-2 (induced by source paper "crowdsourcing a new tool for policy making"):
  with members:
    - "the fundamentals of policy crowdsourcing"
    - "next generation crowdsourcing for collective intelligence"
    - "crowdsourcing sharing economies and development"
    - "crowd science measurements models and methods"
    - "the theory of crowd capital"
    - "the labor economics of paid crowdsourcing"

Connected through hyperedge HE-3 (induced by source paper "crowdsourcing sharing economies and development"):
  with members:
    - "the fundamentals of policy crowdsourcing"
    - "the theory of crowd capital"

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.CY(Computers and Society)