Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election
Throughout the 2016 U.S. presidential election, public debate and media coverage was shaped by so called "fake news" – news articles which were intentionally false, and designed to influence opinion and policy. Although fake news itself is not a new concept, the way in which it was covered...
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ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-890552020-09-29T05:39:34Z Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election Wheaton, Grace Claire Political Science Jewitt, Caitlin E. Hult, Karen M. Jardine, Eric fake news content analysis 2016 election Facebook social media Throughout the 2016 U.S. presidential election, public debate and media coverage was shaped by so called "fake news" – news articles which were intentionally false, and designed to influence opinion and policy. Although fake news itself is not a new concept, the way in which it was covered, and the was it was spread on social media platforms, was. Given this, scholarly literature examining fake news, and specifically the content or stylistic characteristics of fake news, is minimal. My research seeks to address that gap through examining different content characteristics of fake news articles spread on social media in 2016, and testing the impact of those characteristics on Facebook engagement (the number of likes or shares an article received). I find political fake news circulated during the 2016 U.S. election is relatively homogeneous in content: it avoids policy discussion, is highly partisan, and negative in tone. Furthermore, personal content, policy discussion, partisan lean, and article tone have no detectable effect on the engagement received on Facebook. My research serves to provide avenues for future research, and increase our understanding of how fake news is spread. More importantly, given the negative influence fake news has on public discussion and democratic legitimacy, my research also increases our understanding of how to best combat the influence of fake news, and how to limit its spread. Master of Arts Throughout the 2016 U.S. presidential election, public debate and media coverage was shaped by so called “fake news” – news articles which were intentionally false, and designed to influence opinion and policy. Although fake news itself is not a new concept, the way in which it was covered, and the was it was spread on social media platforms, was. Given this, scholarly literature examining fake news, and specifically the content or stylistic characteristics of fake news, is minimal. My research seeks to address that gap through examining different content characteristics of fake news articles spread on social media in 2016, and testing the impact of those characteristics on Facebook engagement (the number of likes or shares an article received). I find political fake news circulated during the 2016 U.S. election is relatively homogeneous in content: it avoids policy discussion, is highly partisan, and negative in tone. Furthermore, personal content, policy discussion, partisan lean, and article tone have no detectable effect on the engagement received on Facebook. My research serves to provide avenues for future research, and increase our understanding of how fake news is spread. More importantly, given the negative influence fake news has on public discussion and democratic legitimacy, my research also increases our understanding of how to best combat the influence of fake news, and how to limit its spread. 2019-04-19T08:00:19Z 2019-04-19T08:00:19Z 2019-04-18 Thesis vt_gsexam:18557 http://hdl.handle.net/10919/89055 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech |
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fake news content analysis 2016 election social media |
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fake news content analysis 2016 election social media Wheaton, Grace Claire Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election |
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Throughout the 2016 U.S. presidential election, public debate and media coverage was shaped by so called "fake news" – news articles which were intentionally false, and designed to influence opinion and policy. Although fake news itself is not a new concept, the way in which it was covered, and the was it was spread on social media platforms, was. Given this, scholarly literature examining fake news, and specifically the content or stylistic characteristics of fake news, is minimal. My research seeks to address that gap through examining different content characteristics of fake news articles spread on social media in 2016, and testing the impact of those characteristics on Facebook engagement (the number of likes or shares an article received).
I find political fake news circulated during the 2016 U.S. election is relatively homogeneous in content: it avoids policy discussion, is highly partisan, and negative in tone. Furthermore, personal content, policy discussion, partisan lean, and article tone have no detectable effect on the engagement received on Facebook. My research serves to provide avenues for future research, and increase our understanding of how fake news is spread. More importantly, given the negative influence fake news has on public discussion and democratic legitimacy, my research also increases our understanding of how to best combat the influence of fake news, and how to limit its spread. === Master of Arts === Throughout the 2016 U.S. presidential election, public debate and media coverage was shaped by so called “fake news” – news articles which were intentionally false, and designed to influence opinion and policy. Although fake news itself is not a new concept, the way in which it was covered, and the was it was spread on social media platforms, was. Given this, scholarly literature examining fake news, and specifically the content or stylistic characteristics of fake news, is minimal. My research seeks to address that gap through examining different content characteristics of fake news articles spread on social media in 2016, and testing the impact of those characteristics on Facebook engagement (the number of likes or shares an article received). I find political fake news circulated during the 2016 U.S. election is relatively homogeneous in content: it avoids policy discussion, is highly partisan, and negative in tone. Furthermore, personal content, policy discussion, partisan lean, and article tone have no detectable effect on the engagement received on Facebook. My research serves to provide avenues for future research, and increase our understanding of how fake news is spread. More importantly, given the negative influence fake news has on public discussion and democratic legitimacy, my research also increases our understanding of how to best combat the influence of fake news, and how to limit its spread. |
author2 |
Political Science |
author_facet |
Political Science Wheaton, Grace Claire |
author |
Wheaton, Grace Claire |
author_sort |
Wheaton, Grace Claire |
title |
Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election |
title_short |
Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election |
title_full |
Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election |
title_fullStr |
Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election |
title_full_unstemmed |
Birthers, Hand Signals, and Spirit Cooking: The Impact of Political Fake News Content on Facebook Engagement during the 2016 Presidential Election |
title_sort |
birthers, hand signals, and spirit cooking: the impact of political fake news content on facebook engagement during the 2016 presidential election |
publisher |
Virginia Tech |
publishDate |
2019 |
url |
http://hdl.handle.net/10919/89055 |
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