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Predicting floods with Flickr tags.

Nataliya Tkachenko1, Stephen Jarvis1,2, Rob Procter1,2

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Summary
This summary is machine-generated.

User-generated content from social media offers denser hazard coverage and documents human impact. This study uses polysemous image tags for early flood warnings, moving beyond simple nowcasting.

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Area of Science:

  • Geospatial Information Science
  • Social Media Analytics
  • Natural Hazard Management

Background:

  • Social media user-generated content (UGC) and metadata provide valuable operational information during natural hazards.
  • UGC offers denser geographical coverage than traditional sensor networks and documents direct human impact.
  • Current social media analytics for hazards are limited to nowcasting due to simplistic tag interpretation.

Purpose of the Study:

  • To explore the use of polysemous tags in social media images for natural hazard analysis.
  • To demonstrate how volunteered geographic data can enable early warning systems for events like floods.
  • To advance beyond the nowcasting limitations of current social media analytics methods.

Main Methods:

  • Analysis of polysemous tags associated with images from social media during flood events.
  • Utilizing volunteered geographic data, including content and metadata, for hazard assessment.
  • Developing methods to interpret diverse social media content (hashtags, images, text, emojis) and metadata (keywords, tags, geolocation).

Main Results:

  • Polysemous tags in social media images contain predictive information for natural hazard events.
  • Volunteered geographic data, when interpreted effectively, can provide insights beyond simple event identification.
  • The study demonstrates a novel approach to leveraging social media for proactive hazard warnings.

Conclusions:

  • Interpreting nuanced social media data, such as polysemous tags, enhances our ability to predict natural hazards.
  • Social media analytics can be advanced from nowcasting to early warning capabilities.
  • This research highlights the potential of UGC for improving disaster preparedness and response.