Beliefs regarding “fake reports”
To respond to that concern, we again analyzed the newest answers victims offered when questioned what fake information and propaganda suggest. I analyzed only those solutions where victims offered a description having possibly label (55%, letter = 162). Remember that the brand new ratio out-of subjects just who given for example definitions was below from inside the Studies step one (95%) and you will 2 (88%). Abreast of better test, i found that numerous subjects got likely pasted definitions off an Internet search. Inside the an enthusiastic exploratory data, we discover a mathematically significant difference from the possibilities you to users provided good pasted meaning, according to Political Identity, ? 2 (2, N = 162) = 7.66, p = 0.022. Specifically, conservatives (23%) was indeed more hookup apps iphone likely than simply centrists (6%) to incorporate a beneficial pasted meaning, ? 2 (step one, N = 138) = eight.29, p = 0.007, Or = 4.57, 95% CI [step one.31, ], some other p philosophy > 0.256. Liberals dropped ranging from these types of extremes, having thirteen% delivering an effective pasted definition. Because we were searching for subjects’ very own definitions, we omitted these doubtful responses out of investigation (letter = 27).
We followed a comparable analytical process as in Studies step one and you may 2. Desk 4 screens this type of investigation. As the desk suggests, the fresh proportions of victims whoever answers incorporated the features explained in the Try step one was in fact comparable across governmental character. Specifically, we don’t replicate the latest trying to find regarding Try out 1, whereby individuals who recognized leftover was in fact more likely to offer independent meanings into conditions than simply those who known right, ? 2 (1, N = 90) = step 1.42, p = 0.233, various other p opinions > 0.063.
Even more 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’ 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-, MRight-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 rGenuine(292) = 0.48, 95% CI [0.39, 0.57]; minimum rReal(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 rBogus(292) = 0.34, 95% CI [0.23, 0.44]; minimum rFake(292) = 0.12, 95% CI [0.01, 0.23]. Only one of the remaining 14 sources-CNN-was negatively correlated, rFake(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.