Keep in mind once more the second number 1 question: To what extent do political identification apply to how somebody translate the newest term “fake reports”?

Keep in mind once more the second number 1 question: To what extent do political identification apply to how somebody translate the newest term “fake reports”?

Beliefs about “phony information”

To resolve that concern, i once again assessed the brand new answers sufferers gave whenever requested just what phony development and you will propaganda mean. I analyzed solely those solutions where sufferers given a classification to own either label (55%, letter = 162). Keep in mind that the ratio off sufferers exactly who given eg meanings try below during the Experiments 1 (95%) and dos (88%). On nearer test, i found that several subjects got most likely pasted significance away from an enthusiastic Internet search. In an exploratory studies, we receive a mathematically significant difference on chances one to users considering an excellent pasted definition, centered on Political Identification, ? 2 (dos, Letter = 162) = seven.66, p = 0.022. Especially, conservatives (23%) had been more likely than just centrists (6%) to incorporate a good pasted meaning, ? 2 (step one, Letter = 138) = 7.29, p = 0.007, Otherwise = 4.57, 95% CI [step one.30, ], various other p philosophy > 0.256. Liberals fell between these extremes, which have 13% delivering a pasted couples seeking men for sex definition. Given that we were trying to find subjects’ individual definitions, i omitted such doubtful solutions out-of study (letter = 27).

We implemented a similar analytic techniques as with Experiments step one and you will dos. Table cuatro displays this type of research. Due to the fact desk suggests, the fresh proportions of subjects whose solutions incorporated the advantages demonstrated inside the Try 1 was indeed equivalent across the political personality. Particularly, i did not replicate the fresh looking from Test step one, where people who recognized left have been very likely to offer independent definitions with the terminology than just those who identified proper, ? 2 (1, N = 90) = step one.42, p = 0.233, almost every other p thinking > 0.063.

Additional 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.