Remember again our very own next no. 1 concern: As to the the total amount really does governmental identification apply at exactly how individuals translate the fresh new term “bogus information”?

Opinions regarding “phony reports”

To respond to one to question, we once again assessed new solutions sufferers gave when expected exactly what phony development and you will propaganda imply. I analyzed only those answers in which sufferers provided a definition to possess often label (55%, letter = 162). Note that the proportion from sufferers exactly who provided eg meanings was below from inside the Studies step 1 (95%) and you will 2 (88%). Upon better examination, i unearthed that several sufferers got more than likely pasted significance out of an Google search. Inside an exploratory research, i found a statistically factor on the probability that members provided an excellent pasted definition, according to Political Identity, ? dos (2, N = 162) = 7.66, p = 0.022. Specifically, conservatives (23%) have been likely to be than centrists (6%) to provide a pasted meaning, ? dos (step one, N = 138) = eight.29, p = 0.007, Or = 4.57, 95% CI [1.29, ], another p opinions > 0.256. Liberals dropped ranging from these types of extremes, that have 13% providing a great pasted definition. Because the we were searching for subjects’ individual significance, i omitted such skeptical responses out-of study (n = 27).

We implemented a comparable analytical processes like in Studies step 1 and dos. Desk 4 screens this type of investigation. As the table shows, the newest proportions of victims whose solutions included the advantages revealed in Try step 1 was basically similar across political personality. Especially, we don’t replicate the fresh looking away from Test step 1, where individuals who understood kept was very likely to give separate meanings with the conditions than those who identified correct, ? 2 (step 1, N = 90) = step 1.42, p = 0.233, any p beliefs > 0.063.

Extra exploratory analyses

We now turn to our additional exploratory analyses specific to this experiment. First, we examine the extent to which people’s reported familiarity with our news sources varies according to their political identification. Liberals and conservatives iliar with different sources, and we know that familiarity can act as a guide in determining what is true (Alter and Oppenheimer 2009). To examine this idea, we ran a two-way Ailiarity, 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). This analysis showed that the influence of political identification on subjects’ https://hookupfornight.com/best-hookup-apps/ familiarity ratings differed across the sources: F(2, 82) = 2.11, p < 0.001, ? 2 = 0.01. Closer inspection revealed that conservatives reported higher familiarity than liberals for most news sources, with centrists falling in-between (Fs range 6.62-, M_Right-Kept range 0.62-1.39, all p values < 0.002). The exceptions-that is, where familiarity ratings were not meaningfully different across political identification-were the media giants: The BBC, CNN, Fox News, Google News, The Guardian, The New York Post, The New York Times, The Wall Street Journal, The Washington Post, Yahoo News, and CBS News.

We also predicted that familiarity with our news sources would be positively associated with real news ratings and negatively associated with fake news ratings. To test this idea, we calculated-for each news source-correlations between familiarity and real news ratings, and familiarity and fake news ratings. In line with our prediction, we found that familiarity was positively associated with real news ratings across all news sources: maximum r_Actual(292) = 0.48, 95% CI [0.39, 0.57]; minimum r_Real(292) = 0.15, 95% CI [0.04, 0.26]. But in contrast with what we predicted, we found that familiarity was also positively associated with fake news ratings, for two out of every three news sources: maximum r_Bogus(292) = 0.34, 95% CI [0.23, 0.44]; minimum r_Fake(292) = 0.12, 95% CI [0.01, 0.23]. Only one of the remaining 14 sources-CNN-was negatively correlated, r_Fake(292) = -0.15, 95% CI [-0.26, -0.03]; all other CIs crossed zero. Taken together, these exploratory results, while tentative, might suggest that familiarity with a news source leads to a bias in which people agree with any claim about that source.