• Corpus ID: 9579658

Detecting and classifying anomalous behavior in spatiotemporal network data ∗

@inproceedings{Young2014DetectingAC,
  title={Detecting and classifying anomalous behavior in spatiotemporal network data ∗},
  author={William Chad Young and Joshua Evan Blumenstock and Emily B. Fox and Tyler H. McCormick},
  year={2014}
}
We investigate different models for detecting and classifying important geopolitical events in high-frequency spatiotemporal network data. Building on previous empirical work on the network response to real-world events, our goal is to develop a generative model that can identify the time, location, and nature of different emergency and non-emergency events. As a testbed for these models, we use a large dataset containing billions of anonymized mobile phone calls and text messages from… 

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