Beliefs regarding the development present
We first tested the newest the total amount that new evaluations out of genuine information, fake reports, and you will propaganda was regarding one another, collapsed across the reports supply. Way more particularly, we calculated the average of any subject’s 42 real information analysis, 42 bogus news feedback, and you can 42 propaganda product reviews. Once the dining table reveals, actual development reviews had been highly and you may negatively of this fake development studies and you will propaganda reviews, and you can bogus information evaluations was indeed firmly and certainly associated with propaganda studies. These study suggest-at the very least for the checklist i made use of-one to information agencies rated extremely because resources of genuine development is actually unlikely are ranked extremely just like the types of phony news or propaganda, and this development firms rated extremely just like the resources of fake reports are likely to be ranked highly since sources of propaganda.
I 2nd classified sufferers toward around three political teams according to the self-stated governmental character. I classified sufferers since the “Left” when they had selected all “left” selection (n = 92), “Center” after they had chosen this new “center” solution (n = 54), and you may “Right” after they got selected some of the “right” alternatives (letter = 57). On analyses that pursue, i discover equivalent habits off results when treating governmental identification because the a continuous variable; our classifications here are with regard to ease of interpretation.
Before turning to our primary questions, we wondered how people’s ratings varied according to political identification, irrespective of news source. To the extent that conservatives believe claims that the mainstream media is “fake news,” we might expect people on the right to have higher overall ratings of fake news and propaganda than their counterparts on the left. Conversely, we might expect people on the left to have higher overall ratings of real news than their counterparts on the right. We display the three averaged ratings-split by political identification-in the top panel of Fig. 2. As the figure shows, our predictions were correct. One-way analyses of variance (ANOVAs) on each of the three averaged ratings, treating Political Identification as a between-subjects factor with three levels (Left, Center, Right), were statistically significant: Real news F(2, 200) = 5.87, p = 0.003, ? 2 = 0.06; Fake news F(2, 200) = , p < 0.001, ? 2 = 0.12; Propaganda F(2, 200) = 7.80, p < 0.001, ? 2 = 0.07. Footnote 2 Follow-up Tukey comparisons showed that people who identified left gave higher real news ratings than people who identified right (Mdiff = 0.29, 95% CI [0.09, 0.49], t(147) = 3.38, p = 0.003, Cohen’s d = 0.492); lower fake news ratings than people who identified right (Mdiff = 0.45, 95% CI [0.24, 0.66], t(147) = 5.09, p < 0.001, d = 0.771) and center (Mdiff = 0.23, 95% CI [0.02, 0.44], t(144) = 2.59, p = 0.028, d = 0.400); and lower propaganda ratings than people who identified right (Mdiff = 0.39, 95% CI [0.15, 0.62], t(147) = 3.94, p < 0.001, d = 0.663). Together, these results suggest that-compared to their liberal counterparts-conservatives generally believe that the news sources included in this study provide less real news, more fake news, and more propaganda.
Mediocre Real development, Bogus information, and you may Propaganda evaluations-split because of the Political character 
. Better panel: 2017 study. Center panel: 2018 research. Bottom committee: 2020 study. Mistake bars depict 95% trust intervals out of mobile means
Abilities and you can discussion
We now turn to our primary questions. First, to what extent does political affiliation affect which specific news sources people consider real news, fake news, or propaganda? To answer that question, we ran two-way ANOVAs on each of the three rating types, treating Political Identification as a between-subjects factor with three levels (Left, Center, Right) and News Source as a within-subject factor with 42 levels (i.e., Table 1). Footnote 3 These analyses showed that the influence of political identification on subjects’ ratings differed across the news sources. All three ANOVAs produced statistically significant interactions: Real news F(2, 82) = 6.88, p < 0.001, ? 2 = 0.05; Fake news F(2, 82) = 7.03, p < 0.001, ? 2 = 0.05; Propaganda F(2, 82) = 6.48, p < 0.001, ? 2 = 0.05.
