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: "an analytical framework to nowcast well being using mobile phone data"
  Abstract: An intriguing open question is whether measurements derived from Big Data recording human activities can yield high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we design a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that the diversity of mobility, defined in terms of entropy of the individual users’ trajectories, exhibits (i) significant correlation with two different socio-economic indicators and (ii) the highest importance in predictive models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through the lens of Big Data by means of new statistical indicators that quantify and possibly “nowcast” the well-being and the socio-economic development of a territory.

Connected through hyperedge HE-1 (induced by source paper "assessing refugees integration via spatio temporal similarities of mobility and calling behaviors"):
  with members:
    - "detecting permanent and intermittent purchase hotspots via computational stigmergy"
    - "data for refugees the d4r challenge on mobility of syrian refugees in turkey"
    - "a stigmergy based analysis of city hotspots to discover trends and anomalies in urban transportation usage"
    - "studying migrant assimilation through facebook interests"
    - "spatio temporal data mining a survey of problems and methods"
    - "stigmergy based modeling to discover urban activity patterns from positioning data"
    - "crisis analytics big data driven crisis response"
    - "mobile communication signatures of unemployment"

Connected through hyperedge HE-2 (induced by source paper "assessing the quality of home detection from mobile phone data for official statistics"):
  with members:
    - "a comparison of spatial based targeted disease containment strategies using mobile phone data"
    - "choosing the right home location definition method for the given dataset"
    - "d4d senegal the second mobile phone data for development challenge"
    - "exploring universal patterns in human home work commuting from mobile phone data"
    - "delineating geographical regions with networks of human interactions in an extensive set of countries"

Connected through hyperedge HE-3 (induced by source paper "data driven generation of spatio temporal routines in human mobility"):
  with members:
    - "the death and life of great italian cities a mobile phone data perspective"
    - "a multilayer approach to multiplexity and link prediction in online geo social networks"
    - "a place focused model for social networks in cities"

Connected through hyperedge HE-4 (induced by source paper "a comparison of spatial based targeted disease containment strategies using mobile phone data"):
  with members:
    - "understanding the influence of all nodes in a network"

Connected through hyperedge HE-5 (induced by source paper "mobile communication signatures of unemployment"):
  with members:
    - "complex systems and a computational social science perspective on the labor market"
    - "tracking employment shocks using mobile phone data"

Connected through hyperedge HE-6 (induced by source paper "modelling individual routines and spatio temporal trajectories in human mobility"):
  with members:
    - "the death and life of great italian cities a mobile phone data perspective"

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)