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Fake news and indifference to scientific fact: President Trump’s confused tweets on global warming, climate change and weather

  • David E. Allen
  • Michael McAleer
Article

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.

Keywords

Sentiment analysis Polarity Climate change Scientific verification Weather 

JEL Classification

A1 C88 C44 Z0 

Notes

Acknowledgements

For financial support, the first author acknowledges the Australian Research Council, and the second author is most grateful to the Australian Research Council, National Science Council, Ministry of Science and Technology (MOST), Taiwan, and the Japan Society for the Promotion of Science.

References

  1. De Vries, A. (2012). Sentiment Package, available at https://github.com/andrie/sentiment/blob/master/DESCRIPTION.

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2018

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsUniversity of SydneySydneyAustralia
  2. 2.Department of FinanceAsia UniversityTaichungTaiwan
  3. 3.School of Business and LawEdith Cowan UniversityPerthAustralia
  4. 4.Discipline of Business AnalyticsUniversity of Sydney Business SchoolSydneyAustralia
  5. 5.Institute of Advanced StudiesYokohama National UniversityYokohamaJapan
  6. 6.Econometric Institute, Erasmus School of EconomicsErasmus University RotterdamRotterdamThe Netherlands
  7. 7.Department of Economic Analysis and ICAEComplutense University of MadridMadridSpain

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