Bear in mind once more our 2nd primary concern: To what the amount do political personality affect exactly how someone translate new name “fake news”?
Thinking regarding the “bogus news”
To respond to one to matter, i once more examined the latest responses victims provided when questioned exactly what fake news and you can propaganda mean. We assessed just those answers in which subjects offered a definition to possess sometimes identity (55%, n = 162). Keep in mind that this new ratio of sufferers who considering instance meanings is less than inside Tests step one (95%) and you may 2 (88%). On better test, i learned that multiple sufferers got almost certainly pasted meanings away from an enthusiastic Internet search. Inside the an enthusiastic exploratory studies, we receive a statistically significant difference throughout the likelihood you to people given an excellent pasted definition, centered on Political Identity, ? 2 (2, N = 162) = eight.66, p = 0.022. Particularly, conservatives (23%) have been probably be than simply centrists (6%) to incorporate a beneficial pasted meaning, ? 2 (1, N = 138) = eight.30, p = 0.007, Or = cuatro.57, 95% CI [1.31, ], every other p beliefs > 0.256. Liberals decrease between such extremes, with thirteen% taking a beneficial pasted meaning. While the we had been seeking subjects’ individual significance, i excluded these doubtful solutions from investigation (letter = 27).
I followed a similar analytical techniques such as Studies 1 and 2. Table 4 screens these types of research. Just like the dining table reveals, the proportions of sufferers whoever answers included the features revealed inside Try out step 1 was equivalent across political identification. Specifically, i don’t replicate the new looking for out-of Try out step one, in which people who known left was in fact likely to offer separate meanings into the conditions than just individuals who understood right, ? 2 (1, N = 90) = 1.42, p = 0.233, virtually any p thinking > 0.063.
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 hookupdaddy.net/couples-hookup-apps 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-Remaining 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 rActual(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 rPhony(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.