Remember again our second number one question: As to what extent do governmental identification apply to just how individuals understand the fresh term “bogus information”?
Values from the “phony reports”
To resolve you to matter, i again reviewed the brand new solutions victims offered when questioned exactly what fake news and you can propaganda indicate. I reviewed solely those answers in which sufferers considering a meaning getting possibly name (55%, n = 162). Keep in mind that the brand new proportion away from sufferers just who given including definitions are lower than in Studies step 1 (95%) and you may dos (88%). Abreast of nearer examination, i found that several subjects got most likely pasted significance out-of an enthusiastic Google search. For the a keen exploratory investigation, we located a statistically significant difference on chances that users given good pasted meaning, centered on Political Identity, ? dos (2, Letter = 162) = 7.66, p = 0.022. Particularly, conservatives (23%) have been probably be than just centrists (6%) to add an excellent pasted meaning, ? dos (step 1, Letter = 138) = 7.29, p = 0.007, Or = cuatro.57, 95% CI [step one.30, ], other p beliefs > 0.256. Liberals decrease anywhere between these types of extremes, which have 13% providing a good pasted meaning. Because the we were looking subjects’ individual significance, i omitted these skeptical responses off data (letter = 27).
I adopted a comparable analytic process as with Tests step 1 and dos. Desk cuatro screens this type of studies. As the table suggests, this new proportions of subjects whose solutions integrated the characteristics discussed inside the Try out step 1 were comparable across the governmental identification. Particularly, i don’t imitate the fresh new selecting off Try out step 1, by which individuals who identified left have been very likely to offer separate significance to the terms than people that recognized proper, ? dos (step one, N = 90) = step one.42, p = 0.233, any p opinions > 0.063.
Most exploratory analyses
We now turn to our additional exploratory analyses specific to this experiment. First, we examine the extent to older men seeking women 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-Left 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 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.
