| Literature DB >> 33782116 |
Andrew M Guess1,2, Pablo Barberá3, Simon Munzert4, JungHwan Yang5.
Abstract
What role do ideologically extreme media play in the polarization of society? Here we report results from a randomized longitudinal field experiment embedded in a nationally representative online panel survey (N = 1,037) in which participants were incentivized to change their browser default settings and social media following patterns, boosting the likelihood of encountering news with either a left-leaning (HuffPost) or right-leaning (Fox News) slant during the 2018 US midterm election campaign. Data on ≈ 19 million web visits by respondents indicate that resulting changes in news consumption persisted for at least 8 wk. Greater exposure to partisan news can cause immediate but short-lived increases in website visits and knowledge of recent events. After adjusting for multiple comparisons, however, we find little evidence of a direct impact on opinions or affect. Still, results from later survey waves suggest that both treatments produce a lasting and meaningful decrease in trust in the mainstream media up to 1 y later. Consistent with the minimal-effects tradition, direct consequences of online partisan media are limited, although our findings raise questions about the possibility of subtle, cumulative dynamics. The combination of experimentation and computational social science techniques illustrates a powerful approach for studying the long-term consequences of exposure to partisan news.Entities:
Keywords: computational social science; media; polarization; politics
Year: 2021 PMID: 33782116 PMCID: PMC8040813 DOI: 10.1073/pnas.2013464118
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205
Fig. 1.Overview of study design. Subjects in wave 3 who were randomly assigned to the Fox News or HuffPost encouragement groups were offered $8 in YouGov incentives to participate in the treatment.
Fig. 2.Weekly average log(number of visits + 1) to (Left) foxnews.com and (Right) huffingtonpost.com by treatment assignment, with 68% (thick lines) and 95% (thin lines) confidence intervals. Behavioral data are from YouGov Pulse panelists.
Fig. 3.Summary of effects (with 95% confidence intervals) on news visits/shares (study 1) and event knowledge (study 2). For visits, coefficients represent effect of treatment assignment on over given time period postintervention. Each visit type (hard news, conservative news, and liberal news) excludes visits to both foxnews.com and huffingtonpost.com. Shares data show containing liberal (HuffPost treatment) or conservative (Fox News treatment) links. Models are fully saturated OLS regressions with indicator variables for browser using preregistered LASSO covariate selection procedure. For event knowledge, standardized coefficients represent CACE estimates from two-stage least squares models in which treatment receipt, measured using web visit data, is instrumented with treatment assignment.
Fig. 4.Summary of effects (with 95% confidence intervals) on issue importance, attitudes, and self-reported behavior. Standardized coefficients represent CACE estimates from two-stage least squares models in which treatment receipt, measured using web visit data, is instrumented with treatment assignment and covariates are selected via LASSO.