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Predicting gasoline shortage during disasters using social media

Author

Listed:
  • Abhinav Khare

    (University at Buffalo)

  • Qing He

    (University at Buffalo
    University at Buffalo)

  • Rajan Batta

    (University at Buffalo)

Abstract

Shortage of gasoline is a common phenomenon during onset of forecasted disasters like hurricanes. Prediction of future gasoline shortage can guide agencies in pushing supplies to the correct regions and mitigating the shortage. We demonstrate how to incorporate social media data into gasoline supply decision making. We develop a systematic approach to examine social media posts like tweets and sense future gasoline shortage. We build a four-stage shortage prediction methodology. In the first stage, we filter out tweets related to gasoline. In the second stage, we use an SVM-based tweet classifier to classify tweets about the gasoline shortage, using unigrams and topics identified using topic modeling techniques as our features. In the third stage, we predict the number of future tweets about gasoline shortage using a hybrid loss function, which is built to combine ARIMA and Poisson regression methods. In the fourth stage, we employ Poisson regression to predict shortage using the number of tweets predicted in the third stage. To validate the methodology, we develop a case study that predicts the shortage of gasoline, using tweets generated in Florida during the onset and post landfall of Hurricane Irma. We compare the predictions to the ground truth about gasoline shortage during Irma, and the results are very accurate based on commonly used error estimates.

Suggested Citation

  • Abhinav Khare & Qing He & Rajan Batta, 2020. "Predicting gasoline shortage during disasters using social media," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 693-726, September.
  • Handle: RePEc:spr:orspec:v:42:y:2020:i:3:d:10.1007_s00291-019-00559-8
    DOI: 10.1007/s00291-019-00559-8
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    References listed on IDEAS

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    Cited by:

    1. Edwards, Dominiqueca R. & Idoko, Faith O. & Vogiatzis, Chrysafis & Davis, Lauren B. & Mirchandani, Pitu, 2023. "Determining optimal fuel delivery strategies under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
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    3. Walter J. Gutjahr & Nilay Noyan & Nico Vandaele & Luk N. Wassenhove, 2020. "Innovative approaches in humanitarian operations," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(3), pages 585-589, September.

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