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

Yoon Kyung Cha, Craig A. Stow

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

We explore how the analysis of web-based data, such as Twitter and Google Trends, can be used to assess the social relevance of an environmental accident. The concept and methods are applied in the shutdown of drinking water supply at the city of Toledo, Ohio, USA. Toledo's notice, which persisted from August 1 to 4, 2014, is a high-profile event that directly influenced approximately half a million people and received wide recognition. The notice was given when excessive levels of microcystin, a byproduct of cyanobacteria blooms, were discovered at the drinking water treatment plant on Lake Erie. Twitter mining results illustrated an instant response to the Toledo incident, the associated collective knowledge, and public perception. The results from Google Trends, on the other hand, revealed how the Toledo event raised public attention on the associated environmental issue, harmful algal blooms, in a long-term context. Thus, when jointly applied, Twitter and Google Trend analysis results offer complementary perspectives. Web content aggregated through mining approaches provides a social standpoint, such as public perception and interest, and offers context for establishing and evaluating environmental management policies. The joint application of Twitter and Google Trend analysis to an environmental event offered both short and long-term patterns of public perception and interest on the event.

Original languageEnglish
Pages (from-to)97-99
Number of pages3
JournalEnvironmental Pollution
Volume198
DOIs
StatePublished - Mar 2015

Keywords

  • Algal blooms
  • Data mining
  • Google trends
  • Public perception and interest
  • Social media
  • Twitter
  • Web search trends

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