Algorithmic social media use and its relationship to attitude reinforcement and issue-specific political participation – The case of the 2015 European immigration movements

ABSTRACT

Selective exposure to likeminded political viewpoints on algorithmic social media platforms is considered a potential source of polarization of public opinion. We still know little about the proposed mechanism or how potential reinforcement of specific attitudes affects citizens’ political behavior, especially in a nonelectoral context. Focusing on the issue of immigration during the refugee influx to Europe in autumn 2015, this study investigates the effects of social media usage on attitude reinforcement, connecting it to political participation in refugee-related activities. A panel study conducted among Danish citizens (n = 847) reveals that frequent social media usage reinforces existing attitudes and mobilizes political participation. However, citizens who become more extreme in their attitude toward immigration over time are found to be less likely to become politically active regarding this specific issue.

KEYWORDS:

• Social media
• attitude polarization
• political participation
• immigration
• reinforcing spirals model (RSM)

Notes

1. Of the 13,700 people, 1,700 were also recruited via the pollster’s database.

2. Goodness of fit tests were used to test for sample differences between the original sample (N = 9125) and study participants (n = 847) regarding gender (n.s.), age (> 5.1 years, p <.001), political interest (> 0.6, p <.001, Min = 0, Max = 10), mobile Internet use (> 3,2%, p <.001) and social media use (n.s.)

3. To be sure, that reported values are not dependent on the frequency of participation in the diary study, we tested for differences between all respondents who participated 4–7 days (n = 633) and 8–10 days (n = 650). No significant differences exist for offline media sources (M =.40 vs. M =.44, t(1282) = −2.54, p =.06), nonalgorithmic online sources (M =.10 vs. M =.10, t(1282) = −.29, p =.61), and algorithmic social media sources (M =.13 vs. M =.12, t(1282) =1.42, p =.07).

4. Adding immigration attitude as the original 5-point scale to the same model yields consistent results: Immigration attitude at t1 significantly predicts the same attitude at t2 (β =.761, SE =.023, p <.001)

5. (0 = no reinforcement, 1 = positive reinforcement (n = 34); negative reinforcement excluded from the analysis)

6. (0 = no reinforcement, 1 = negative reinforcement (n = 43); positive reinforcement excluded from the analysis)

Additional information

Funding

This work was supported by the Syddansk Universitet.

Notes on contributors

Jakob Ohme

Jakob Ohme is a Postdoctoral Researcher at the Amsterdam School of Communication Research (ASCoR), University of Amsterdam. As part of the Digital Communication Method Lab, he develops and tests new mobile methodological approaches to study media exposure and its effects on political behavior and civic attitudes.