Detecting Climate Change Deniers on Twitter Using a Deep Neural Network-Reference-Cited by-同舟云学术

Detecting Climate Change Deniers on Twitter Using a Deep Neural Network

Published:2019 Issue: Volume: Page:
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Container-title:Proceedings of the 2019 11th International Conference on Machine Learning and Computing - ICMLC '19
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Author:

Chen Xingyu¹,Zou Lei²,Zhao Bo³

Affiliation:

1. Shanghai Maritime University, Shanghai, China

2. Texas A&M University, Texas, USA

3. Oregon State University, Corvallis, Oregon, USA

Publisher

ACM Press

Reference11 articles.

1. NASA, https://www.nasa.gov/audience/forstudents/k-4/stories/nasa-knows/what-is-climate-change-k4.html

2. Leiserowitz et al. Climate change in the American mind: March 2018" Yale University and George Mason University. New Haven, CT: Yale Program on Climate Change Communication.

3. Wildman, Steve, and Jonathan A. Obar. Social Media Definition and the Governance Challenge: An Introduction to the Special Issue. www.academia.edu, http://www.academia.edu/14293577/Social_Media_Definition_and_the_Governance_Challenge_An_Introduction_to_the_Special_Issue. Accessed 7 Dec. 2018.

4. Kryvasheyeu, Yury, et al. Rapid Assessment of Disaster Damage Using Social Media Activity. Science Advances, vol. 2, no. 3, Mar. 2016, p. e1500779. advances.sciencemag.org, doi:10.1126/sciadv.1500779.

5. Kirilenko, Andrei P., and Svetlana O. Stepchenkova. Public Microblogging on Climate Change: One Year of Twitter Worldwide. Global Environmental Change, vol. 26, May 2014, pp. 171--82. ScienceDirect, doi:10.1016/j.gloenvcha.2014.02.008.

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