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 truth: Dissecting tweets and State of the Union Addresses by Presidents Obama and Trump
Abstract: State of the Union Addresses (SOUA) by two recent US Presidents, President Obama (2016) and President Trump (2018), and a series of recent of tweets 
	by President Trump, 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 di_er, and their potential implications for the national mood and state of the economy. President 
	Trump's 2018 SOUA and his sample tweets are identi_ed as being more positive in sentiment than President Obama's 2016 SOUA. This is con_rmed by 
	bootstrapped t tests and non-parametric sign tests on components of the respective sentiment scores. The issue of whether overly positive 
	pronouncements amount to self-promotion, rather than intrinsic merit or sentiment, is a topic for future research.
Classification-JEL: A1, C88, C44, Z0.
Keywords: Sentiment Analysis, Polarity, Bootstrapped tests, Sign tests.
Length: 23 pages 
Creation-Date: 2018-03
Number: 2018-07
X-File-Ref: http://america.sim.ucm.es/repec/ucm/ref/doicae1807.txt
File-URL: https://eprints.ucm.es/id/eprint/46802/1/1807.pdf
File-Format: Application/pdf
Handle: RePEc:ucm:doicae:1807