Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll.
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.
Computational Story Lab, University of Vermont, Burlington, VT 05401, United States of America; Vermont Complex Systems Center, University of Vermont, Burlington VT 05401, United States of America; Department of Mathematics and Statistics, University of Vermont, Burlington VT 05401, United States of America.
Emily M
EM
Cody
Computational Story Lab, University of Vermont, Burlington, VT 05401, United States of America; Vermont Complex Systems Center, University of Vermont, Burlington VT 05401, United States of America; Department of Mathematics and Statistics, University of Vermont, Burlington VT 05401, United States of America.
Andrew J
AJ
Reagan
School of Mathematical Sciences, The University of Adelaide, SA 5005, Australia.
Lewis
L
Mitchell
Computational Story Lab, University of Vermont, Burlington, VT 05401, United States of America; Vermont Complex Systems Center, University of Vermont, Burlington VT 05401, United States of America; Department of Mathematics and Statistics, University of Vermont, Burlington VT 05401, United States of America.
Peter Sheridan
PS
Dodds
Computational Story Lab, University of Vermont, Burlington, VT 05401, United States of America; Vermont Complex Systems Center, University of Vermont, Burlington VT 05401, United States of America; Department of Mathematics and Statistics, University of Vermont, Burlington VT 05401, United States of America.
Christopher M
CM
Danforth
D057231:Climate Change; D004190:Disasters; D057232:Global Warming; D006240:Happiness; D006801:Humans; D011639:Public Opinion; D061108:Social Media / Q000706:statistics & numerical data*