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 "estimating local commuting patterns from geolocated twitter data"):
  Abstract: The emergence of large stores of transactional data generated by increasing use of digital devices presents a huge opportunity for policymakers to improve their knowledge of the local environment and thus make more informed and better decisions. A research frontier is hence emerging which involves exploring the type of measures that can be drawn from data stores such as mobile phone logs, Internet searches and contributions to social media platforms, and the extent to which these measures are accurate reflections of the wider population. This paper contributes to this research frontier, by exploring the extent to which local commuting patterns can be estimated from data drawn from Twitter. It makes three contributions in particular. First, it shows that simple heuristics drawn from geolocated Twitter data offer a good proxy for local commuting patterns; one which outperforms the major existing method for estimating these patterns (the radiation model). Second, it investigates sources of error in the proxy measure, showing that the model performs better on short trips with higher volumes of commuters; it also looks at demographic biases but finds that, surprisingly, measurements are not significantly affected by the fact that the demographic makeup of Twitter users differs significantly from the population as a whole. Finally, it looks at potential ways of going beyond simple heuristics by incorporating temporal information into models.

Includes members:
  Member "predicting human mobility through the assimilation of social media traces into mobility models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "facebook ads as a demographic tool to measure the urban rural divide")
  Member "wikipedia traffic data and electoral prediction towards theoretically informed models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "novel version of pagerank cheirank and 2drank for wikipedia in multilingual network using social impact")
  Member "geo located twitter as proxy for global mobility patterns":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transfer learning from an auxiliary discriminative task for unsupervised anomaly detection")
  Member "uncovering patterns of inter urban trip and spatial interaction from social media check in data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "depicting urban boundaries from a mobility network of spatial interactions a case study of great britain with geo located twitter data")
  Member "where in the world are you geolocation and language identification in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a hierarchical location prediction neural network for twitter user geolocation")
  Member "multi scale population and mobility estimation with geo tagged tweets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "creating full individual level location timelines from sparse social media data")
  Member "is the sample good enough comparing data from twitter s streaming api with twitter s firehose":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sampling on networks estimating spectral centrality measures and their impact in evaluating other relevant network measures")

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)