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: "wearable computing for health and fitness exploring the relationship between data and human behaviour"
  Abstract: Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise when relating this to long term mention of wearable devices. Previous studies within this area are discussed. We also consider a new approach where data is used to support instead of motivate, through monitoring and logging to encourage reflection. Based on issues highlighted, we then make recommendations on the direction in which future work could be most beneficial.

Connected through hyperedge HE-1 (induced by source paper "i ll be back on the multiple lives of users of a mobile activity tracking application"):
  with members:
    - "how gamification affects physical activity large scale analysis of walking challenges in a mobile application"
    - "online actions with offline impact how online social networks influence online and offline user behavior"
    - "donor retention in online crowdfunding communities a case study of donorschoose org"
    - "engaging with massive online courses"

Connected through hyperedge HE-2 (induced by source paper "next generation crowdsourcing for collective intelligence"):
  with members:
    - "the fundamentals of policy crowdsourcing"
    - "the contours of crowd capability"
    - "how to work a crowd developing crowd capital through crowdsourcing"
    - "crowd science measurements models and methods"
    - "reliable diversity based spatial crowdsourcing by moving workers"
    - "prediction based task assignment on spatial 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)