Partisanship, Propaganda, and Disinformation: Online Media and the 2016 U.S. Presidential Election

By Robert Faris, H. Roberts, Bruce Etling, N. Bourassa, Ethan Zuckerman, Yochai Benkler. 2017

Subfields: AI Ethics, Fairness & Society, Social Sciences & Humanities

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In AI Ethics, Fairness & Society

1. Ali Farhadi
2. Yejin Choi
3. David G. Rand
4. Rowan Zellers
5. Gordon Pennycook
6. Jieun Shin

In Social Sciences & Humanities

1. Ali Farhadi
2. Yejin Choi
3. Sumitra Badrinathan
4. David G. Rand
5. Hannah Rashkin
6. Gordon Pennycook
7. Jieun Shin

Citations in the corpus

• Defending Against Neural Fake News (2019, background): “Malicious actors spread fallacious viral stories in order to gain advertising revenue, influence opinions, and even tip elections (Faris et al., 2017; Wardle and Derakhshan, 2017).”
• Reasoning Over Semantic-Level Graph for Fact Checking (2019, background): “However, malicious people spread false news, which may have significant in-fluence on public opinions, stock prices, even presidential elections (Faris et al., 2017).”
• Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward (2021, background): “Because of the extensive usage of social media, Hyper-partisan media is one of the biggest potential incubators for spreading fabricated news among the people [29].”
• The diffusion of misinformation on social media: Temporal pattern, message, and source (2018, background): “Disinformation False To gain an advantage Jack (2017); Faris et al. (2017) Misinformation False Unknown Lewandowsky et al. (2012) Rumor Unknown Unknown Bordia & DiFonzo (2007); Rojecki & Meraz, 2016; Shin et al. (2017) Fake news False To gain an advantage Silverman (2017); Vargo et al. (2017) Troll…”
• Educative Interventions to Combat Misinformation: Evidence from a Field Experiment in India (2020, background): “Although everyone is vulnerable to misinformation to a certain extent, worldview backfire effects are more visible for Republicans but not Democrats, given that the insular nature of the conservative media system is more conducive to the spread of misinformation (Faris et al. 2017; Ecker and Ang 201”
• The Psychology of Fake News. (2021, unknown): “Misleading hyperpartisan news, as well as yellow journalism [5], are related forms of problematic news content that are likely sources of political polarization [6].”
• Exposure to opposing views on social media can increase political polarization (2018, unknown): “Although our findings should not be generalized beyond partyidentified Americans who use Twitter frequently, we note that recent studies indicate this population has an outsized influence on the trajectory of public discussion—particularly as the media itself has come to rely upon Twitter as a sourc”
• Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning. (2019, unknown): “Much has been made of the potential effect that fake news had on voting for the 2016 US Presidential election (e.g., Allcott & Gentzkow, 2017; Faris et al., 2017; Lazer et al., 2018); the underlying presumption is that people are, in fact, responsive to fake news in important ways.”
• Fighting misinformation on social media using crowdsourced judgments of news source quality (2019, background): “Second, news consumption patterns vary markedly across the political spectrum (16) and it has been argued that political partisans are motivated consumers of misinformation (17).”