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: "predicting human mobility through the assimilation of social media traces into mobility models"
  Abstract: Predicting human mobility flows at different spatial scales is challenged by the heterogeneity of individual trajectories and the multi-scale nature of transportation networks. As vast amounts of digital traces of human behaviour become available, an opportunity arises to improve mobility models by integrating into them proxy data on mobility collected by a variety of digital platforms and location-aware services. Here we propose a hybrid model of human mobility that integrates a large-scale publicly available dataset from a popular photo-sharing system with the classical gravity model, under a stacked regression procedure. We validate the performance and generalizability of our approach using two ground-truth datasets on air travel and daily commuting in the United States: using two different cross-validation schemes we show that the hybrid model affords enhanced mobility prediction at both spatial scales.

Connected through hyperedge HE-1 (induced by source paper "facebook ads as a demographic tool to measure the urban rural divide"):
  with members:
    - "human values and attitudes towards vaccination in social media"
    - "analyzing gender inequality through large scale facebook advertising data"
    - "predicting demographics moral foundations and human values from digital behaviours"
    - "parents mention sons more often than daughters on social media"
    - "effect of values and technology use on exercise implications for personalized behavior change interventions"
    - "demographic differentials in facebook usage around the world"
    - "a total error framework for digital traces of humans"
    - "mater certa est pater numquam what can facebook advertising data tell us about male fertility rates"

Connected through hyperedge HE-2 (induced by source paper "measuring spatial subdivisions in urban mobility with mobile phone data"):
  with members:
    - "shopping mall attraction and social mixing at a city scale"
    - "estimating local commuting patterns from geolocated twitter data"

Connected through hyperedge HE-3 (induced by source paper "estimating local commuting patterns from geolocated twitter data"):
  with members:
    - "wikipedia traffic data and electoral prediction towards theoretically informed models"
    - "geo located twitter as proxy for global mobility patterns"
    - "uncovering patterns of inter urban trip and spatial interaction from social media check in data"
    - "where in the world are you geolocation and language identification in twitter"
    - "multi scale population and mobility estimation with geo tagged tweets"
    - "is the sample good enough comparing data from twitter s streaming api with twitter s firehose"

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)