How Do People Describe Locations During a Natural Disaster: An Analysis of Tweets from Hurricane Harvey

Authors Yingjie Hu , Jimin Wang

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Yingjie Hu
  • GeoAI Lab, Department of Geography, University at Buffalo, NY, USA
Jimin Wang
  • GeoAI Lab, Department of Geography, University at Buffalo, NY, USA

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Yingjie Hu and Jimin Wang. How Do People Describe Locations During a Natural Disaster: An Analysis of Tweets from Hurricane Harvey. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 6:1-6:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


Social media platforms, such as Twitter, have been increasingly used by people during natural disasters to share information and request for help. Hurricane Harvey was a category 4 hurricane that devastated Houston, Texas, USA in August 2017 and caused catastrophic flooding in the Houston metropolitan area. Hurricane Harvey also witnessed the widespread use of social media by the general public in response to this major disaster, and geographic locations are key information pieces described in many of the social media messages. A geoparsing system, or a geoparser, can be utilized to automatically extract and locate the described locations, which can help first responders reach the people in need. While a number of geoparsers have already been developed, it is unclear how effective they are in recognizing and geo-locating the locations described by people during natural disasters. To fill this gap, this work seeks to understand how people describe locations during a natural disaster by analyzing a sample of tweets posted during Hurricane Harvey. We then identify the limitations of existing geoparsers in processing these tweets, and discuss possible approaches to overcoming these limitations.

Subject Classification

ACM Subject Classification
  • Information systems → Content analysis and feature selection
  • Information systems → Retrieval effectiveness
  • Geoparsing
  • geographic informational retrieval
  • social media
  • tweet analysis
  • disaster response


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