Template-type: ReDIF-Paper 1.0
Author-Name: David E. Allen
Author-Workplace-Name: School of Mathematics and Statistics, University of Sydney, Australia, Department of Finance, Asia University, Taiwan, and School of Business and Law, 
	Edith Cowan University, Western Australia.

Author-Name:
 Michael McAleer
Author-Workplace-Name:
 Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of 
	Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of 
	Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.
Author-Name: David McHardy Reid
Author-Workplace-Name: Albers School of Business and Economics, Seattle University, Washington, USA.

Title: Fake News and Indifference to Scientific Fact: President Trump's Confused Tweets on Global Warming, Climate Change and Weather
Abstract: A set of 115 tweets on climate change by President Trump, from 2011 to 2015, are analysed by means of the data mining technique, sentiment analysis. The intention is 
	to explore the contents and sentiments of the messages contained the degree to which they differ, and their implications about his understanding of climate change. The 
	results suggest a predominantly negative emotion in relation to tweets on climate change, but they appear to lack a clear logical framework, and confuse short term 
	variations in localised weather with long term global average climate change.
Classification-JEL: A1, C44, C88, Z0.
Keywords: Sentiment Analysis; Polarity; Climate Change; Scientific Verification; Weather.
Length: 8 pages 
Creation-Date: 2018-05
Number: 2018-17
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1817.txt
File-URL: https://eprints.ucm.es/id/eprint/47902/1/1817.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1817