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Mining web-based data to assess public response to environmental events.

YoonKyung Cha1, Craig A Stow2

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Analyzing social media and search trends can gauge public reaction to environmental accidents. This study used Twitter and Google Trends to assess the social relevance of Toledo

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Area of Science:

  • Environmental Science
  • Public Health
  • Data Science

Background:

  • Environmental accidents can significantly impact public health and require effective management strategies.
  • Assessing the social relevance of such events is crucial for understanding public perception and informing policy.

Purpose of the Study:

  • To explore the utility of web-based data analysis, specifically Twitter and Google Trends, for assessing the social relevance of environmental accidents.
  • To apply these methods to the 2014 Toledo drinking water crisis caused by harmful algal blooms.

Main Methods:

  • Utilized Twitter mining to analyze real-time public response, collective knowledge, and perception during the Toledo incident.
  • Employed Google Trends analysis to understand long-term public attention shifts related to the environmental issue (harmful algal blooms).
  • Integrated both data sources to provide complementary social perspectives on the environmental event.

Main Results:

  • Twitter mining revealed immediate public reactions and collective understanding following the Toledo water crisis.
  • Google Trends demonstrated sustained public interest in harmful algal blooms post-incident, indicating heightened environmental awareness.
  • The combined analysis offered a comprehensive social viewpoint on the event's impact and relevance.

Conclusions:

  • Web data mining, through platforms like Twitter and Google Trends, provides valuable insights into the social dimensions of environmental accidents.
  • These methods offer a social standpoint, capturing public perception and interest, which is essential for environmental policy development and evaluation.
  • The joint application of Twitter and Google Trends analysis yields complementary perspectives for a holistic understanding of environmental events.