| Literature DB >> 35360473 |
Desiree Steppat1, Laia Castro Herrero1, Frank Esser1.
Abstract
Previous research posits that individual predispositions play an essential role in explaining patterns of selective exposure to political information. Yet the contextual factors in the political information environment have received far less attention. Using a cross-national and quasi-experimental design, this article is one of the first to investigate how political information environments shape selective exposure. We rely on a unique two-wave online survey quasi-experiment in five countries (Switzerland, Denmark, Italy, Poland and the United States) with 4349 participants to test the propositions that (a) the level of polarization and fragmentation in information environments and (b) the type of media source used affect selective exposure. Our results reveal that selective exposure is slightly more frequent among regular social media users but is less common among users of TV, radio and newspapers; crucially, it is more common in information environments that are highly fragmented and polarized. Nevertheless, news users from less fragmented-polarized media landscapes show one surprising yet intriguing behaviour: in a quasi-experimentally manipulated setting with more opportunities to self-select than they may be accustomed to, their coping strategy is to pick larger amounts of congruent news stories. All our findings imply that contextual factors play a crucial role in moderating individuals' tendency to select information that aligns with their political views.Entities:
Keywords: International comparison; media fragmentation; media polarization; news; political information environment; selective exposure
Year: 2021 PMID: 35360473 PMCID: PMC8958559 DOI: 10.1177/02673231211012141
Source DB: PubMed Journal: Eur J Commun ISSN: 0267-3231
Figure 1.Three indicators of media fragmentation.
(1) Market size refers to the proportion of population above 14 years old that uses news on a regular basis. (2) Non-PSB audience refers to the share other (private) TV stations have on the market apart from the main PSBs. (3) Non-shared news refers to the proportion of news users not using the main news media outlet in the respective countries.
Figure 2.Two indicators of media polarization.
(1) Political parallelism is a standardized measure taking into account the following categories: amount of commentary, partisan policy, journalists’ political orientation, media-party parallelism, political bias and PSB dependency. (2) Audience polarization takes into account the average distance of the political orientation from the audience of the five most used news outlets per media type from the average political orientation in each country (as weighted by audience share).
Figure 3.Cross-country differences for three selective exposure measures (ANCOVA).
Predicted average levels of self-reported, perceived and actual selective exposure by country. All three selective exposure measures were rescaled on a 0–1 scale to make them comparable. (1) Self-reported SE: F(4, 3448) = 32.44, p < .001, η2 = .036. (2) Perceived SE: F(4, 3080) = 6.32, p < .001, η2 = .008. (3) Actual SE: F(4, 3465) = 3.43, p < .01, η2 = .004. Groups with different identification letters (a, b, c) are significantly different according to Bonferroni-corrected post hoc tests (p < .05).
Bootstrapped OLS regression with three selective exposure measures.
| Self-reported selective exposure | Perceived selective exposure | Actual selective exposure | ||||
|---|---|---|---|---|---|---|
| B | SE B | B | SE B | B | SE B | |
| (Constant) | 2.479 | .086 | 9.251 | .295 | .057 | .074 |
| Sex (baseline male) | .030 | .021 | .018 | .010 | −.012 | .021 |
| Age | .000 | .002 | .001 | .002 | .002 | .001 |
| Education | .033 | .031 | .097 | .066 | −.031 | .010 |
| Political interest | .033 | .013 | .057 | .026 | −.013 | .007 |
| Political orientation | .004 | .005 | −.075 | .027 | .015 | .002 |
| Political extremity | .083 | .076 | −.655 | .042 | .012 | .005 |
| Predictors #1 - #4 | ||||||
| | .405 | .059 | .204 | .099 | −.047 | .024 |
| #2 TV user | −.092 | .062 | −.137 | .095 | −.066 | .024 |
| #3 Radio user | −.014 | .023 | −.013 | .091 | −.021 | .082 |
| #3 Newspaper user | −.042 | .025 | −.063 | .097 | .022 | .027 |
| #4 Social media user | .073 | .029 | −.02 | .037 | −.017 | .011 |
|
| 2812 | 2560 | 2825 | |||
|
| .101 | .270 | .018 | |||
|
| 299.48 | 804.78 | 51.04 | |||
OLS: ordinary least squares.
Estimates are unstandardized coefficients (B) with standard errors (SE B).
p < .001, **p < .01, *p < .05, †p < .1 (two-tailed).