human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "assessing refugees integration via spatio temporal similarities of mobility and calling behaviors"):
  Abstract: In Turkey, the increasing tension, due to the presence of 3.4 million Syrian refugees, demands the formulation of effective integration policies. Moreover, their design requires tools aimed at understanding the integration of refugees despite the complexity of this phenomenon. In this work, we propose a set of metrics aimed at providing insights and assessing the integration of Syrian refugees, by analyzing a real-world call detail record (CDR) dataset including calls from refugees and locals in Turkey throughout 2017. Specifically, we exploit the similarity between refugees’ and locals’ spatial and temporal behaviors, in terms of communication and mobility in order to assess integration dynamics. Together with the already known methods for data analysis, we use a novel computational approach to analyze spatio-temporal patterns: computational stigmergy, a bio-inspired scalar and temporal aggregation of samples. Computational stigmergy associates each sample with a virtual pheromone deposit (mark). Marks in spatiotemporal proximity are aggregated into functional structures called trails, which summarize the spatiotemporal patterns in data and allow computing the similarity between different patterns. According to our results, collective mobility and behavioral similarity with locals have great potential as measures of integration, since they are: 1) correlated with the amount of interaction with locals; 2) an effective proxy for refugee’s economic capacity, and thus refugee’s potential employment; and 3) able to capture events that may disrupt the integration phenomena, such as social tension.

Includes members:
  Member "detecting permanent and intermittent purchase hotspots via computational stigmergy":
    also connected through other hyperedges:
      (none)
  Member "data for refugees the d4r challenge on mobility of syrian refugees in turkey":
    also connected through other hyperedges:
      (none)
  Member "a stigmergy based analysis of city hotspots to discover trends and anomalies in urban transportation usage":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "detecting permanent and intermittent purchase hotspots via computational stigmergy")
  Member "studying migrant assimilation through facebook interests":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "facebook ads as a demographic tool to measure the urban rural divide")
  Member "spatio temporal data mining a survey of problems and methods":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "semi supervised classification using attention based regularization on coarse resolution data")
  Member "stigmergy based modeling to discover urban activity patterns from positioning data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "stigmergic independent reinforcement learning for multi agent collaboration")
  Member "crisis analytics big data driven crisis response":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "caveat emptor the risks of using big data for human development")
  Member "mobile communication signatures of unemployment":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "estimating socioeconomic status via temporal spatial mobility analysis a case study of smart card data")

Question: Please tell me which class the source paper 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)