Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll

PLoS One. 2015 Aug 20;10(8):e0136092. doi: 10.1371/journal.pone.0136092. eCollection 2015.

Abstract

The consequences of anthropogenic climate change are extensively debated through scientific papers, newspaper articles, and blogs. Newspaper articles may lack accuracy, while the severity of findings in scientific papers may be too opaque for the public to understand. Social media, however, is a forum where individuals of diverse backgrounds can share their thoughts and opinions. As consumption shifts from old media to new, Twitter has become a valuable resource for analyzing current events and headline news. In this research, we analyze tweets containing the word "climate" collected between September 2008 and July 2014. Through use of a previously developed sentiment measurement tool called the Hedonometer, we determine how collective sentiment varies in response to climate change news, events, and natural disasters. We find that natural disasters, climate bills, and oil-drilling can contribute to a decrease in happiness while climate rallies, a book release, and a green ideas contest can contribute to an increase in happiness. Words uncovered by our analysis suggest that responses to climate change news are predominately from climate change activists rather than climate change deniers, indicating that Twitter is a valuable resource for the spread of climate change awareness.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Climate Change*
  • Disasters
  • Global Warming
  • Happiness
  • Humans
  • Public Opinion*
  • Social Media / statistics & numerical data*

Grants and funding

The authors are grateful for the computational resources provided by the Vermont Advanced Computing Core which is supported by the Vermont Complex Systems Center. CMD, AJR, EMC, and LM were supported by National Science Foundation (NSF) grant DMS-0940271 to the Mathematics & Climate Research Network. PSD was supported by NSF CAREER Award #0846668.