Sage Journals: Discover world-class research

Abstract

The policy of free movement—one of the core principles of the European Union—has become increasingly politicized. This makes it more important to understand how attitudes toward free movement are shaped, and the role of the media. The purpose of this study is therefore to investigate how news frames affect attitudes toward free movement, and whether education moderates framing effects. The findings from a survey experiment conducted in seven European countries show that the effects are few and inconsistent across countries. This suggest that these attitudes are not easily shifted by exposure to a single news frame.

Keywords

framing effects attitudes toward free movement survey experiment cross-national research

The European Union (EU) policy of free movement entitles EU citizens to move to and freely take up employment in other member states. Although free movement is one of the core principles of the EU, this policy has become increasingly politicized over the last years. In richer EU countries, economic difficulties in many member states seem to have led to concerns about a mass influx of workers, while in poorer countries, worries about a “brain drain” of highly skilled workers who leave the country have emerged (Barbulescu, 2017; González-Ferrer & Moreno-Fuentes, 2017; Ienciu & Ienciu, 2015; Vasilopoulou & Talving, 2019). The issue also contributed to the outcome of the Brexit referendum (Goodwin & Milazzo, 2017; Hobolt, 2016).

In light of this, it has become increasingly important to understand how public attitudes toward free movement are shaped. In that context, there are reasons to believe that the media matter. To begin with, extant research suggests that media can have significant effects on public attitudes in general (Maurer, 2014). Second, research indicates that media might matter in particular with respect to issues that are perceived to be complex and abstract, which applies to EU politics (de Vreese & Boomgaarden, 2006). Third, extant research shows that media might influence attitudes on related issues, including both EU policies (Vliegenthart et al., 2008) and migration (Eberl et al., 2018). Altogether, this suggests that media may have an impact on attitudes toward free movement within the EU.

Aside from the question of whether media have an impact on attitudes toward free movement, of importance is also how media effects on free movement attitudes arise. In that context, there are at least three aspects that are likely to matter. First, it is reasonable to assume that the valence of the news frames is a central factor. There are indications that people who immigrate from other EU countries tend to be portrayed as threats to the economy and welfare of the host countries, while positive coverage is less prevalent (Balch & Balabanova, 2016; Eberl et al., 2018). Evidence also suggests that media frames focusing on negative economic implications of immigration tend to lead to more negative attitudes toward immigration and increased support for restrictive immigration policies, while positive framing is likely to contribute to more positive attitudes (Eberl et al., 2018). Since free movement stimulates intra-EU migration, it is plausible that framing effects on immigration attitudes extend to free movement attitudes.

Second, whether the frame is episodic or thematic can also play a key role in shaping free movement attitudes. Research suggests that episodic frames—compared with thematic frames—are more emotionally engaging as well as easier to recall and less demanding to process (Gross, 2008; Iyengar, 1991; Springer & Harwood, 2015). Research also indicates that news stories focusing on people’s personal experiences (which episodic frames tend to do), rather than statistics and overviews of official information (which thematic frames often utilize), are more powerful in influencing attitudes (Brosius, 1999). Hence, episodic frames might be more effective than thematic frames in shaping free movement attitudes.

Third, media may not only influence attitudes toward free movement by highlighting positive or negative aspects of intra-EU immigration but also by emphasizing positive or negative aspects of intra-EU emigration. Concern about people leaving the country is substantial in some EU states (González-Ferrer & Moreno-Fuentes, 2017; Ienciu & Ienciu, 2015; Mazza & Soto, 2019), which is likely to make people receptive to media reports about the implications of emigration. Moreover, González-Ferrer and Moreno-Fuentes (2017) suggest that oversimplified and problem-oriented media coverage of emigration can affect people’s perceptions of emigration. To our knowledge, this notion has however not been empirically tested yet.

It is important to note, however, that media effects are seldom universal. Instead, they tend to depend on a range of individual-level factors (Valkenburg & Peter, 2013). In the context of free movement, one individual-level factor that might moderate media effects is education, since research suggests that education impacts attitudes toward free movement (Scheve & Slaughter, 2001; Vasilopoulou & Talving, 2019; Vergeer et al., 2000), as well as media effects on attitudes toward immigration (Schmuck & Matthes, 2015).

In light of this, the purpose of this study is to investigate whether and how different news frames affect attitudes toward free movement with special attention to the moderating role of education. Toward this end, we rely on an experiment where we manipulate a news article by varying the valence of the frame (positive vs. negative), the type of frame (episodic vs. thematic), and the type of intra-EU migration (emigration vs. immigration). In contrast to most experimental studies, we furthermore employ a design including seven countries: Germany, Hungary, Poland, Romania, Spain, Sweden, and the United Kingdom. Thereby, we will be able to test the robustness of the results.

Media Frames in the Context of Migration and the EU

Theoretically, this study departs from framing theory. This is still a rather fragmented research field with some dissensus regarding what exactly constitutes framing (Entman et al., 2009; Lecheler & de Vreese, 2018). Important in this context is the distinction between equivalence frames and emphasis frames. Whereas equivalence framing refers to logically identical content that is presented or phrased differently, emphasis framing can involve one set of facts or arguments to the exclusion of other facts or arguments and thus present qualitatively different content (Cacciatore et al., 2016; Lecheler & de Vreese, 2018). In the present study, we follow the emphasis framing tradition by focusing on the effects of news frames from a positive versus negative perspective and thematic versus episodic perspective. The rationale behind the decision to focus on emphasis framing is that (a) emphasis frames are closer to “real” journalistic news coverage than equivalence frames (Lecheler & de Vreese, 2018), leading to higher external validity, and (b) studies focusing on media frames in the context of migration and the EU tend to focus on emphasis frames by, for instance, comparing the effects of different types of “threat frames” and “benefit frames” (e.g., de Vreese et al., 2011; Igartua et al., 2011). Using the same approach as previous studies thus enables comparisons and exploration of the generalizability of findings from previous studies.

The Influence of Positive and Negative News Media Frames

According to the intergroup threat theory, opposition to immigration is likely to be based on perceived symbolic threats—such as threats to the cultural identity and values—or perceived realistic threats—such as threats to the economy or physical well-being (Stephan et al., 2009; Stephan & Stephan, 2000). Research suggests that threat perceptions can be triggered by negative news frames (Igartua et al., 2011). For example, research suggests that frames that link immigration to negative implications—for example, impact on the culture, economy, and physical threats such as terrorism and crime—are likely to generate more negative attitudes, while news stories highlighting positive implications are likely to have more positive effects (Igartua & Cheng, 2009; Lahav & Courtemanche, 2012).

Notably, many studies within the migration literature have found that opposition to immigration stems more from perceived symbolic than from perceived realistic threats (e.g., Hainmueller & Hopkins, 2014, for an overview). For free movement attitudes, the situation might however be different. As intra-EU migrants’ culture and ethnic background generally differ less from that of the host society than the culture and ethnic background of migrants coming from countries outside the EU, immigrants from other EU countries are likely to elicit fewer negative reactions stemming from symbolic threats (e.g., Dustmann & Preston, 2007; Ford, 2011). In addition, it is reasonable to assume that realistic threats are more central when it comes to intra-EU migration, in particular since the economy and labor market competition has been the focus of public debate about mobility within the EU (Ienciu & Ienciu, 2015; Ruhs, 2017; Vasilopoulou & Talving, 2019).

Moreover, evidence suggests that media frames focusing on negative implications of migration on the economy and labor market can generate negative attitudes toward immigration and immigrants (Costello & Hodson, 2011; Schmuck & Matthes, 2017). It is not too far-fetched to expect that this also holds true when it comes to attitudes toward free movement. At the same time, it should be noted that the effects might differ depending on whether the media coverage is about migration within the EU or immigration from other regions. European integration—that mainly has come about through the EU and its policies—might foster sentiments of closer connection to Europeans in other member states (Pichler, 2009). In line with this, research suggests that some people in European societies express a so-called “European cosmopolitism” by feeling close to other Europeans in addition to the people within the national-state (Bruter, 2004; Pichler, 2009). It might therefore be more difficult for media to move (especially negative) attitudes toward migration within the EU, compared with attitudes toward migration from other parts of the world. At the same time, the expectation that negative frames are likely to lead to more negative attitudes toward free movement is supported by evidence from a cross-national experiment, showing that support for free movement declines when people are exposed to information suggesting that immigration from other EU countries leads to labor market and welfare risks (Karstens, 2019).¹ Moreover, the expectation about more negative attitudes as a consequence of negative frames is in line with evidence from a comparative study based on panel data and a content analysis. Specifically, this study shows that exposure to negative news frames on migration can stimulate more negative attitudes toward free movement (Meltzer et al., 2020).

There is also some evidence suggesting that an “economic benefit frame” (e.g., increase in labor force as a consequence of immigration) generates more positive attitudes toward immigration compared with a negative news frame (Igartua & Cheng, 2009). However, it should be noted that most previous studies do not include a control group in the experiments (Igartua & Cheng, 2009; Igartua et al., 2011). Therefore, it remains unclear whether people who are exposed to positive frames are likely to develop more positive attitudes than people who do not get any information, or more positive attitudes compared with people who are exposed to negative frames. There are, however, some indications that positive frames are less powerful than negative frames. For instance, de Vreese and colleagues (2011) found that there was a significant difference in attitudes among respondents who received the negative economic frame and respondents in the control group, while no significant difference was identified between those who received the economic benefit frame and those in the control group. This finding is in line with research suggesting that negative information, in general, stimulates stronger effects than positive information (Cobb & Kuklinski, 1997; Schemer, 2014). Hence, our first hypotheses are:

H1a: News frames focusing on negative implications of free movement on the economy and labor market will lead to more negative attitudes toward free movement than news frames focusing on positive implications.

H1b: News frames focusing on positive implications of free movement on the economy and labor market will have weaker effects on attitudes toward free movement than news frames focusing on negative implications.

Thematic Versus Episodic Frames

Aside from valence, the distinction between thematic and episodic frames might be important for understanding framing effects on free movement attitudes. In general, thematic frames place issues in general contexts, for example, by presenting statistics or other information about the overall status of the issue under consideration. Episodic frames, in contrast, focus on exemplars and stories from individuals whose experiences exemplify an issue (Daschmann & Brosius, 1999; Iyengar, 1991, 1996; Springer & Harwood, 2015).

Importantly, the personal exemplars that are a key element of episodic frames do not necessarily illustrate representative cases. Instead, they are often selected for their vividness, entertaining, dramatic, or sensational qualities, and to make issues more accessible (Brosius, 1999; Zillmann et al., 1996). This can be understood in light of media logic, where personalization—the tendency to focus on individual actors—is a central technique used to capture attention (Strömbäck & Esser, 2015).

In general, research suggests that episodic frames are more emotionally engaging than thematic frames, which might be a result of the personal connection that people feel with the person in the episodic news story and the fact that it might be less demanding to process episodically framed media messages (Gross, 2008; Iyengar, 1991; Springer & Harwood, 2015). Exemplification research also suggests that people rely more on personal exemplars than on rather abstract overviews to evaluate the overall conditions of an issue (Zillmann et al., 1996; Zillmann, 2002). In fact, research indicates that exemplars are likely to influence attitudes more than the type of content that is often used in thematic frames, such as statistics, expert opinions, and overviews of official information—even when the latter is more valid (Daschmann & Brosius, 1999). This has been explained by the fact that exemplars are easier to interpret, remember, and process—especially when it comes to issues that are likely to attract attention and evoke emotions (Zillmann, 2002).

Arguably, migration-related issues may be examples of issues where the use of episodic frames are especially powerful, as they are likely to evoke emotions (such as a feeling of outgroup fear in response to news on immigration). In addition, since thematic frames are typically more abstract, they may be less persuasive than episodic frames. Based on this, we expect that:

H2a: Negative episodic news frames will lead to more negative attitudes toward free movement than negative thematic news frames.

H2b: Positive episodic news frames will lead to more positive attitudes than positive thematic news frames.

The Moderating Role of Education

Realistic group conflict theory (Campbell, 1965) suggests that social groups have to compete with each other in acquiring scarce goods and that people in less privileged socioeconomic positions—similar to the ones of many ethnic minorities—are especially likely to perceive that they have to compete with immigrants (e.g., about jobs and wages) and feel threatened by immigration. Consistent with this, research suggests that less educated people exhibit more negative attitudes toward immigration than highly educated people (Scheve & Slaughter, 2001; Vergeer et al., 2000).

In addition, those with higher education tend to be more positive toward the EU, as well as free movement, compared with less educated people. It is also worth noting that research suggests that education is a stronger predictor for EU support and free movement attitudes compared with other demographic factors such as age and gender (Hakhverdian et al., 2013; Vasilopoulou & Talving, 2019).

According to Vasilopoulou and Talving (2019), one reason why free movement might be viewed as more threatening among people with lower levels of education is that they are less equipped for successfully competing in a changing and competitive labor market, than those with higher education. They also suggest that the well-educated utilize free movement the most by moving from one EU member state to another. Since highly educated people hold more positive attitudes from the start and utilize the benefits connected to free movement to a greater extent, it is reasonable to expect that they are more resistant to negative news frames about the implications of free movement. That would be in line with research suggesting that people are less likely to accept counter-attitudinal information than congenial information (Druckman et al., 2012).

It should also be noted that highly educated and politically knowledgeable citizens, in general, are likely to be more resistant to media messages (Biek et al., 1996; Cao, 2008; Schemer, 2012; Zaller, 1992). One reason is that these individuals tend to use their knowledge to critically evaluate new incoming information. They are also more likely to use their knowledge to defend existing attitudes (Zaller, 1992). Furthermore, evidence suggests that education might moderate media effects on attitudes toward immigration (Huber & Lapinski, 2006; Schmuck & Matthes, 2015). For instance, Schmuck and Matthes (2015) found that a political advertisement that framed immigration as an economic threat led to more negative attitudes among less educated, while it did not have any effect on higher educated people.

Against this background, we expect that highly educated individuals will be less affected by news frames focusing on negative implications of free movement.²

H3: News frames focusing on negative implications of free movement on the economy and labor market will lead to more negative attitudes toward free movement among people with a low level of education than among people with a high level of education.

It might, however, be the case that this moderating effect differs depending on whether the news story frames the free movement issue by focusing on labor immigration or emigration. Individuals with lower levels of education might, for instance, be more positive toward emigration than immigration, as emigration may be viewed as an opportunity to go abroad to increase the chances of finding a job, while immigration might be thought of as something that increases the competition on the labor market. Therefore, negative news stories about immigration may be more effective in reinforcing negative attitudes. That being said, we expect negative articles focusing on immigration as well as emigration to have a larger impact on people with lower levels of education than on people with higher education. Yet, since the effects might differ depending on whether the news story is about immigration or emigration, we formulate a research question:

RQ1: Does the moderation effect of education differ depending on if the news story is about labor immigration or labor emigration?

Finally, we expect the level of education to moderate the effect of episodically framed articles. As mentioned, episodic frames are less demanding to process. While this might be less important for highly educated who are better equipped for processing more abstract and complex information, it may be more relevant for the less educated. This might lead to more negative attitudes for negative episodically framed, compared with negative thematically framed news, among the lower educated. Thus, we expect that:

H4: The negative episodic frames will be more effective in stimulating negative attitudes toward free movement among people with a low level of education, while the effects will differ less between the educational groups for the thematic frames.

Cross-National Variations in Framing Effects?

Following previous theory and research, the above hypotheses could be expected to hold true across countries. That said, many of the cited studies are based on experiments, and these are usually done within single-country settings. At the same time, there are always a number of contextual factors that differ across countries, which might lead to cross-national variations in framing effects. To avoid falsely assumed universality (Blumler & Gurevitch, 1995; Dogan & Pelassy, 1984), it is hence important to test the robustness of any findings across national settings. Thus, our second research question is:

RQ2: Are there cross-national variations in framing effects on attitudes toward free movement?

Data and Method

To test the above hypotheses and answer the research questions, we employed a comparative experimental design, where we vary the valence of the frame, the type of frame, and the type of intra-EU migration. Specifically, the experiment is a random 2 (positive vs. negative frame) × 2 (thematic vs. episodic frame) × 2 (immigration vs. emigration) in-between-subjects design plus one control condition (Theorin et al., 2020).³ Extracts from the beginning section of the different news articles are provided in Table A1 in the Online Appendix.

The experimental design provides the opportunity to investigate the causal effects of specific frames on free movement attitudes, and thus offers a better understanding of how media influence these attitudes. By exposing respondents to the same experimental stimulus across countries, we also avoid the problem that media effects are difficult to compare across countries since media outlets, their content, and contexts differ (Boomgaarden & Song, 2019).

Although it is beyond the scope of this study to investigate the impact of contextual factors that might condition framing effects on free movement attitudes, we aimed to create variation regarding contextual factors that might have an impact, such as socioeconomic conditions, migration flows, EU membership history, attitudes toward immigration, media system, and political culture. Based on this, the following countries were selected: Germany, Hungary, Poland, Romania, Spain, Sweden, and the United Kingdom. Testing the hypotheses and research questions in this diverse set of countries enables us to explore whether potential media effects are universal or whether the effects rather are country-specific.

Participants

The experiment was administrated by the international survey company OPINION & IMPACT in collaboration with Dynata, and conducted between September 5 and 24, 2019. In each country, quota definitions were based on gender and age to ensure accurate estimations of the populations. In total, 8,457 respondents participated (about 1,200 per country).⁴ The sample is largely representative of citizens in EU member states with respect to gender, age, and education, although the highly educated are slightly overrepresented.⁵

Procedure

First, respondents answered questions about control variables, such as ideology and political interest. Thereafter, each respondent was randomly assigned to read one fictional online news article about the impact of labor immigration or labor emigration within the EU as a consequence of free movement. To avoid the risk that respondents would proceed with the survey before reading the article they were assigned, the “next” button was displayed only after 20 seconds. After reading one of the articles, respondents were introduced to the treatment and credibility check, measures on attitudes toward free movement, and sociodemographics, followed by a debriefing.⁶

Stimulus Material

The fictional articles either addressed negative implications of immigration or emigration, such as exploitation of workers, undercutting of wages (immigration conditions), and labor shortages (emigration conditions), or positive implications, such as increased flexibility and decreased labor shortages (immigration conditions), and reduced unemployment (emigration conditions). Furthermore, the articles were either framed episodically—focusing on a citizen’s personal experience of intra-EU migration—or thematically, providing official information from a researcher about the general implications of intra-EU migration. Already in the headline of each article, it was indicated whether the article was positive or negative, and episodic or thematic. For instance, the headline of the English version of the negative episodic article was: “Callum Williams, unemployed: Immigration has severely worsened my work situation,” and the headline of the negative thematic article was: “Immigration has a severely negative impact on the UK economy” (see Table A1 in the Online Appendix for more detailed information).⁷

The different articles were structured in the same way (heading, introduction, quotes, etc.), and designed to look like screenshots of real online news articles. The picture that belonged to the news articles showed several flags of EU member states and silhouettes of people in motion (illustrating intra-EU migration). The same picture was chosen for all experimental conditions and across countries. However, to maximize the cross-national comparability, the flag of the respective country was at the center of the image, and the name of the person featured in the article was changed to a common name in the country. For instance, the name in the U.K. versions was Callum Williams, and the name in the German versions was Jörg Bauer (see Figure A1 and Figure A2 in the Online Appendix).

Measures

Attitudes toward free movement were measured with four items that were linked to the stimulus material, focusing on the economy and labor market: The movement of individuals between EU countries should be (a) restricted to protect workers born in [country], (b) free to deal with labor shortages, (c) free to promote economic growth, and (4) restricted to avoid undercutting of wages (1 = strongly disagree, 5 = strongly agree). Statements 1 and 4 were reverse coded. Based on these items, an index was then constructed (α = .80. M = 3.39. SD = 0.90), where a higher value indicates more favorable attitudes.

Education was measured based on the highest completed level of education. We used local International Standard Classification of Education (ISCED) codes in each country. Thereafter, a correspondence table provided by United Nations Educational, Scientific, and Cultural Organization (UNESCO) was used to match the country-specific codes to its corresponding ISCED level (ranging from 0 = early childhood education to 8 = doctoral or equivalent). Based on this, a dichotomous education variable was created, where 0 refers to low education and equals ISCED Level 0 to 3 (early childhood education–upper secondary education), and 1 refers to high education and equals ISCED Level 6 to 8 (bachelor or equivalent–doctoral or equivalent).

Moreover, we controlled for age and left-right predisposition. Age is important to control for since it is likely to predict susceptibility to attitude change as well as immigration attitudes and EU support (Schotte & Winker, 2018; Vasilopoulou & Talving, 2019; Visser & Krosnick, 1998). Left-right predisposition, in turn, is also linked to immigration attitudes, and research furthermore suggests that people might rely on their left-right predisposition to make sense of frames about migration-related topics (Lahav & Courtemanche, 2012; Pardos-Prado, 2011).

Randomization and Manipulation Checks

The randomization check revealed no significant differences between respondents in the different groups with respect to age⁸ (p = .138, f = 1.54), gender (p = .205, f = 1.37), education (p = .654, f = 0.74), and political ideology (p = .941, f=.36). Second, a manipulation check was conducted. This was done by comparing how respondents answered two questions about the article they had just read: (a) If the article was positive or negative, and (b) If the article focused on immigration or emigration. Results showed that there were significant differences in the expected direction between the groups (p < .001 with respect to both questions).

Third, a credibility check was conducted.⁹ Overall, respondents perceived all articles to be rather authentic, interesting, convincing, and credible. Notably, however, respondents who received a positively framed article about immigration generally perceived the article to be slightly more authentic, interesting, convincing, and credible. This pattern holds true both when comparing answers on the different credibility questions and when using an index based on the different credibility questions.

When comparing respondents in the seven countries, they rated the articles fairly similarly. Yet, there were some cross-national differences. Overall, the articles were perceived as most credible in Poland and Romania and least credible in Hungary and Sweden. That being said, the main conclusion is that although there were some significant credibility differences between experimental groups, these differences were quite modest. Moreover, it is no major surprise that there are some variations since the discourse about free movement is likely to differ across countries.¹⁰

Statistical Analyses

To test the hypotheses and answer the research questions about news framing effects on attitudes toward free movement, a series of ordinary least squares (OLS) regression analyses were performed. All analyses were conducted in Stata 16.

Results

Turning to the results, Table 1, Model 1, shows that respondents exposed to the negatively framed articles did not exhibit more negative attitudes than those exposed to positively framed articles. Moreover, Model 2 in Table 1 shows that neither respondents exposed to negative frames, nor respondents exposed to positive frames, differed significantly from respondents in the control condition. Thus, H1a and H1b are not supported.

Table 1.

Effects of Positive and Negative Frames on Attitudes Toward Free Movement (OLS).

DV: Attitudes toward free movement	Model 1	Model 2
Negative frames (vs. positive frames)	−.013 (.020)
Negative frames (vs. control)		.028 (.048)
Positive frames (vs. control)		.041 (.048)
Adjusted R-square	.118	.117
N	7,464	7,809

Note. Standard errors in parentheses. Dependent variable Attitudes toward free movement is measured on a scale from 1 to 5 (1 = negative attitudes, 5 = positive attitudes). Country differences were controlled for by including country dummy variables (using the United Kingdom as reference category). OLS = ordinary least squares; DV = dependent variable.

p < .05. **p < .01. ***p < .001.

Turning to H2a and H2b, which suggested that negative episodic news frames would lead to more negative attitudes toward free movement than negative thematic news frames (H2a), and that positive episodic news frames would lead to more positive attitudes than positive thematic news frames (H2b), results do not support these expectations. As shown in Table 2, no difference between the negative (positive) episodic frame conditions and the negative (positive) thematic frames was identified.

Table 2.

Effects of Episodic and Thematic Frames on Attitudes Toward Free Movement (OLS).

DV: Attitudes toward free movement	Model 1	Model 2
Negative episodic frames (vs. negative thematic frames)	−.045 (.028)
Positive episodic frames (vs. positive thematic frames)		.012 (.028)
Adjusted R-square	.120	.117
N	3,746	3,718

Note. Standard errors in parentheses. Dependent variable Attitudes toward free movement is measured on a scale from 1 to 5 (1 = negative attitudes, 5 = positive attitudes). Country differences were controlled for by including country dummy variables (using the United Kingdom as reference category). OLS = ordinary least squares; DV = dependent variable.

p < .05. **p < .01. ***p < .001.

Model 2 in Table 3 furthermore shows that there was no interaction effect between education and exposure to the negative immigration frames. Likewise, no interaction effect was identified regarding the emigration frames, as shown in Table 4, Model 2. Hence, H3 is not supported, and the answer to RQ1—asking whether the moderation effect differs depending on whether the frames focus on immigration or emigration—is that the effects did not differ.

Table 3.

Interaction Effect of Negative Immigration Frames (OLS).

DV: Attitudes toward free movement	Model 1	Model 2
Negative immigration frames (vs. control)	.048 (.055)	.018 (.075)
Education	.296 (.037)***	.239 (.103)*
Negative immigration frames × Education		.065 (.109)
Adjusted R-square	.154	.154
N	2,412	2,412

Note. Standard errors in parentheses. Dependent variable Attitudes toward free movement is measured on a scale from 1 to 5 (1 = negative attitudes, 5 = positive attitudes). Country differences were controlled for by including dummy variables for the different countries (using the United Kingdom as reference category). OLS = ordinary least squares; DV = dependent variable.

p < .05. **p < .01. ***p < .001.

Table 4.

Interaction Effect of Negative Emigration Frames (OLS).

DV: Attitudes toward free movement	Model 1	Model 2
Negative emigration frames (vs. control)	.124 (.060)*	.104 (.085)
Education	.285 (.052)***	.256 (.099)**
Negative emigration frames × Education		.039 (.114)
Adjusted R-square	.102	.101
N	1,111	1,111

Note. Standard errors in parentheses. Dependent variable Attitudes toward free movement is measured on a scale from 1 to 5 (1 = negative attitudes, 5 = positive attitudes). Country differences were controlled for by including country dummy variables for the different countries (using Spain as reference category). OLS = ordinary least squares; DV = dependent variable.

p < .05. **p < .01. ***p < .001.

Finally, H4 predicted that the negative episodic frames would be more effective in stimulating negative attitudes toward free movement among those with a low level of education, while the effects would differ less between educational groups for the thematic frames. The findings are displayed in Table 5 and suggest that no interaction effects were identified. Thus, H4 must also be rejected.

Table 5.

Interaction Effects of Episodic Versus Thematic Negative Frames (OLS).

DV: Attitudes toward free movement	Model 1	Model 2	Model 3	Model 4
Negative episodic frames (vs. control)	.048 (.055)	.018 (.075)
Education	.310 (.043)***	.256 (.102)*	.289 (.043)***	.224 (.103)*
Negative episodic frames × Education		.063 (.110)
Negative thematic frames (vs. control)			.070 (.055)	.034 (.076)
Negative thematic frames × Education				.077 (.100)
Adjusted R-square	.136	.136	.842	.152
N	1,770	1,770	1,753	1,753

Note. Standard errors in parentheses. Dependent variable Attitudes toward free movement is measured on a scale from 1 to 5 (1 = negative attitudes, 5 = positive attitudes). Country differences were controlled for by including dummy variables for the different countries (using the United Kingdom as reference category). The positive conditions are not included in these analyses since the focus is on the effects of the negative frames. OLS = ordinary least squares; DV = dependent variable.

p < .05. **p < .01. ***p < .001.

Cross-National Variations in Framing Effects?

Thus far, the results show no support for our hypotheses. It could, however, be the case that there are effects in some but not in other countries. To explore this, RQ2 asked whether the framing effects differ across countries. Analyzing this, we find mixed results. With respect to H1, about the effects of positive versus negative frames, the results show that there were significant effects in Spain but not in the other countries. More specifically, Table A2 in the Online Appendix shows that in Spain, respondents who read a negative article reported more negative attitudes compared with those who read a positive article (B = −.114, p = .022). However, respondents exposed to negative frames exhibited more positive attitudes compared with the control group (B, negative conditions = .245, p = .048). Yet, respondents who received positive frames differed the most from the control group (B = .359, p = .004), which is an indication that the positive frames produced stronger effects than the negative frames in Spain—contradicting H1b.

With respect to H2, about the effects of the episodic versus thematic frames, the results (Table A3 in the Online Appendix) show that in Spain, exposure to negative episodic frames led to more negative attitudes than negative thematic frames (B = −.144, p = .040). However, there was no difference between exposure to positive episodic and positive thematic frames in Spain, and no differences between these two frame types in the other countries.

Finally, we tested H3 and H4—about the moderating effects of education—in each country. The results are provided in Tables A4 to A6 in the Online Appendix. Table A5 shows that respondents with lower levels of education exposed to negative articles about emigration became more negative than highly educated in Romania (B = .757, p = .007). Furthermore, Table A6 shows that in Romania, the negative episodic frames stimulated more negative attitudes toward free movement among those with a lower level of education (B = .683, p = .019), while there was no such effect for the thematic frames. These effects were not observed in any of the other countries. Moreover, education did not moderate the effect of exposure to the negative frames focusing on immigration in any of the countries (Table A4). Overall then, there were some cross-national differences, but the general pattern of results remains, that is, the framing effects are few, weak, and not robust across countries.

Additional Analyses

As a robustness check, we re-ran all analyses, excluding respondents who failed in the attention checks by answering that the person in the article was a woman (in reality it was a man) or that they did not know. In total, 3012 respondents were excluded from these analyses (on average 430 per country). Using this sample did not substantially change the results however, with two exceptions: (a) the difference between the positive as well as the negative frames and the control group became insignificant in Spain. Yet, the negative frames still led to significantly more negative attitudes than the positive frames (B = −.121, p = .046), and (b) the expectation that the positive episodic news frames would lead to more positive attitudes than positive thematic news frames (H2b) was then supported in Sweden (B = .410, p = .002).

As another robustness check and to further investigate variations between educational groups, we also conducted the interaction analyses (H3 and H4) using the original scale variable on education (0 = early childhood education, 8 = doctoral degree or equivalent) and using the margins command in Stata. Again, the analyses based on the scale variable did not change the results, however, with one exception: the finding that less educated respondents exposed to negative articles about emigration became more negative than highly educated in Romania became insignificant. All the results based on the attention check sample, as well as the scale variable on education, are available on request.

Conclusions and Discussion

The starting point for this study was that the media, by means of their framing, could be expected to influence people’s attitudes toward free movement within the EU. Despite the fact that the hypotheses were firmly based on framing theory and previous findings, the main conclusion of the current study is that the framing effects were few, weak, and not robust across countries. Some effects were found—more specifically, that negatively framed articles led to more negative attitudes than positively framed articles in Spain, that negative episodic articles led to more negative attitudes than negative thematic articles in Spain, that negatively framed articles about emigration led to more negative attitudes among less educated in Romania (when the dichotomous education variable was used), and that the negative and episodically framed articles stimulated more negative attitudes toward free movement among those with a low education level in Romania, while there was no such moderation effect for the thematic frames—but this does not change the overall pattern.

This raises the question of why the results showed few framing effects, and why there were not more cross-national differences despite the diverse set of countries included in the study. One answer might be weaknesses in the methodology and design of the present study. It might, for instance, be that the experimental manipulation did not work as intended. However, the experimental treatment was similar to treatments that have generated effects on immigration attitudes and EU-related issues in other studies. Our analyses also show that the credibility- and manipulation checks worked. This speaks for the robustness of the results, although it cannot be ruled out that the experimental manipulations generally were too weak to generate framing effects.

Another answer might be that although numerous studies have shown that media can have effects on public attitudes, this is not always the case (Shehata & Falasca, 2014; Theorin & Strömbäck, 2020). People are equipped with several sources of resistance to media influence (Blinder & Jeannet, 2017; Pomerantz et al., 1995; Slothuus & de Vreese, 2010; Taber & Lodge, 2006). Important in that context is that strong and crystalized attitudes reduce the likelihood of media effects (Pomerantz et al., 1995; Tesler, 2015; Zaller, 1992) while people tend to be more easily influenced by the framing of new issues where the attitudes and the interpretations of the issue have not yet been settled (Chong & Druckman, 2007a). The fact that free movement within the EU has been in place for several decades and that it has been widely debated over the years might thus limit the scope for framing effects. In other words, it might be the case that people are quite familiar with the pro and con arguments of intra-EU migration, which decreases the likelihood that reading a single additional news story influences their attitudes.

Moreover, European integration and sentiments of connections with other Europeans might make the public more resistant toward media coverage about free movement within the EU compared with media coverage about migration from other regions. This does, however, not mean that media frames do not affect the public when it comes to free movement. Chong and Druckman (2007b) argue that even when prior attitudes attenuate framing effects at the time of measurement, this does not tell us that framing, in general, has weak effects, as the prior attitudes themselves may have resulted from a previous diffusion of media frames. To investigate such dynamics, future research needs to broaden the perspective to long-term content analyses on media frames and respective effects on public opinion.

Still, one might ask why the results are inconsistent with previous research, which has found more clear-cut framing effects on related issues such as immigration attitudes. One possible explanation might be publication bias, meaning that the publication of studies is influenced by the significance or directions of the findings (Franco et al., 2014; Gerber et al., 2010) and that studies showing no effects have a harder time getting published. Although it is uncertain whether there is such publication bias in research on framing effects related to migration and the EU, it cannot be ruled out.

Furthermore, the inconsistency with previous research may be due to the rather broad definition of emphasis frames. Cacciatore et al. (2016) claim that a loose (emphasis-based) definition of frames might contribute to making framing effects appear more powerful than they really are as they overlap with other media effect theories. Thus, the authors argue for a more rigid (equivalence-based) definition of framing. We believe that the authors have a valid point, and firmer operationalizations would also simplify the comparison between studies. On the other hand, as previously mentioned, emphasis frames are closer to “real” journalistic news coverage than equivalence frames, which is why most studies—including the current one—have focused on emphasis frames (Lecheler & de Vreese, 2018).

Having said that, the lack of hypothesized effects and inconsistent findings does not equal a lack of results. Our study adds empirical nuances to the research field focusing on how media influence migration- and EU-related attitudes, by showing that news framing does not always move opinions. The fact that we did not find support for the prediction that negative frames would provide stronger effects than positive frames is an interesting finding that deserves to be discussed further. One potential explanation for this is that migration-related issues are more often negatively framed than positively framed. Thus, people might have become more accustomed to these frames, which in turn may decrease their impact on attitudes. That would be in line with research on habituation, suggesting that repeated exposure to the same stimulus can decrease people’s response to that stimulus (Potter, 2012).

Another finding that should be discussed is the insignificant effect of episodic versus thematic frames in the majority of our analyses. This could be understood in light of migration studies suggesting that people’s immigration attitudes are based on perceptions of the economic impact on the nation as a whole (sociotropic evaluation) rather than on perceptions of how immigration affects their personal situation (egocentric evaluation) (Hainmueller & Hiscox, 2010; Hainmueller & Hopkins, 2014; Valentino et al., 2017). Although research suggests that exemplars—a key feature of episodic frames—are likely to influence people’s perceptions about overall conditions as well (Daschmann & Brosius, 1999), it may be that respondents recognized that the thematic articles provided more information about national implications, which might have canceled out the stronger effects that exemplars tend to have. The fact that we only found one moderating effect of education is also consistent with research suggesting that immigration attitudes are based on perceptions of national rather than personal consequences.

Although we identified fewer framing effects than expected, this does not preclude that media can have framing effects on free movement attitudes. It might, for instance, be that stronger reinforcement effects would occur if respondents could choose whether they wanted to read a positive or negative article. Moreover, although we found few effects of being exposed to one news frame, there might be effects of repeated exposure to the same frame. That would be consistent with findings in a panel study on how media influence public opinion about EU enlargement (de Vreese & Boomgaarden, 2006). Specifically, the study found that a substantial level of rather one-sided message flow (positive or negative) influenced public opinion, whereas a more mixed information flow did not.

It might also be that the effects would differ if people got exposed to frames about Roma EU migrants—who are often depicted as economic threats (Meeusen & Jacobs, 2017)—compared with frames about, for instance, Danish EU migrants. Finally, whereas few moderating effects of education were found, other factors might influence the relationship between news frames and free movement attitudes. For instance, it would be interesting to investigate the role of political knowledge since evidence suggest that it is one of the most important individual-level moderators for framing effects (Lecheler & de Vreese, 2018). There is also evidence showing that those with lower issue-specific knowledge are more likely to be influenced by news stories about migrants (Schemer, 2012). Moreover, prior attitudes might play a moderating role: In line with previous research (Druckman et al., 2012), it is plausible to expect that negative (positive) attitudes about free movement are more easily reinforced among individuals who are negative (positive) from the start, and that stronger attitudes are more resistant to change.

Since free movement is a fundamental principle of the EU, research on the media’s role in shaping attitudes toward free movement is of high societal relevance, and further research that addresses these kinds of questions is thus clearly needed.

Supplemental Material

sj-docx-1-jmq-10.1177_10776990211006793 – Supplemental material for Does News Frame Affect Free Movement Attitudes? A Comparative Analysis

Supplemental material, sj-docx-1-jmq-10.1177_10776990211006793 for Does News Frame Affect Free Movement Attitudes? A Comparative Analysis by Nora Theorin, Christine E. Meltzer, Sebastian Galyga, Jesper Strömbäck, Christian Schemer, Jakob-Moritz Eberl, Fabienne Lind, Tobias Heidenreich and Hajo G. Boomgaarden in Journalism & Mass Communication Quarterly

Footnotes

Acknowledgements

We thank Per Alm at the Department of Journalism, Media and Communication, University of Gothenburg, for editing the fictional news articles.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Horizon 2020 Framework Programme (grant number 727072).

ORCID iDs

Nora Theorin

Christian Schemer

Fabienne Lind

Supplemental Material

Supplemental material for this article is available online.

Notes

Author Biographies

Nora Theorin (MA, University of Gothenburg) is a predoctoral researcher at the Department of Journalism, Media and Communication, University of Gothenburg. Her research interests include media effects, public opinion, and migration.

Christine E. Meltzer (PhD, Johannes Gutenberg-University Mainz) is a postdoctoral researcher at the Department of Communication, Johannes Gutenberg-University Mainz. Her research interests include political communication, media and migration, and cultivation research.

Sebastian Galyga (MA, University of Vienna, is a research associate at University of Vienna. His research interests include experimental research, political communication, and manual and automated quantitative content analysis.

Jesper Strömbäck (PhD, Stockholm University) is a professor in journalism and political communication at University of Gothenburg. His research interests include political communication, media effects, and knowledge resistance.

Christian Schemer (PhD, University of Zurich) is a professor in communication at Johannes Gutenberg-University Mainz. His research interests include media representations of social groups, the effects of media portrayals of social troups on intergroups attitudes, and methods of communication science.

Jakob-Moritz Eberl (PhD, University of Vienna) is a postdoctoral researcher at the Department of Communication, University of Vienna. His research interests include the role of media discourses and media bias in shaping public opinion and influencing political behavior.

Fabienne Lind (MA, University of Vienna) is a predoctoral researcher at the Department of Communication, University of Vienna. Her research interests include political communication and quantitative methods with a focus on quantitative text analysis.

Tobias Heidenreich (MA, University of Vienna) is a predoctoral researcher at the Department of Communication, University of Vienna. His research interests include quantitative text analysis, political communication, and social media.

Hajo G. Boomgaarden (PhD, University of Amsterdam) is a professor in text analysis at University of Vienna. His research interest include analysis of news media coverage and its effects on political cognitions, attitudes and behavior.

References

Balch

Balabanova

(2016). Ethics, politics and migration: Public debates on the free movement of Romanians and Bulgarians in the UK, 2006–2013. Politics, 36(1), 19–35. https://doi.org/10.1111/1467-9256.12082

Barbulescu

(2017). From international migration to freedom of movement and back? Southern Europeans moving north in the era of retrenchment of freedom of movement rights. In Lafleur

J.-M.

Stanek

(Eds.), South-North migration of EU citizens in times of crisis (pp. 15–31). Springer.

Biek

Wood

Chaiken

(1996). Working knowledge, cognitive processing, and attitudes: On the determinants of bias. Personality and Social Psychology Bulletin, 22(6), 547–556. https://doi.org/10.1177/0146167296226001

Blinder

Jeannet

A.-M.

(2017). The “illegal” and the skilled: Effects of media portrayals on perceptions of immigration in Britain. Journal of Ethnic and Migration Studies, 44(9), 1444–1462. https://doi.org/10.1080/1369183X.2017.1412253

Blumler

J. G.

Gurevitch

(1995). The crisis of public communication. Routledge.

Boomgaarden

H. G.

Song

(2019). Media use and its effects in a cross-national perspective. Kölner Zeitschrift für Soziologie und Sozialpsychologie, 71, 545–571. https://doi.org/10.1007/s11577-019-00596-9

Brosius

H.-B.

(1999). The influence of exemplars on recipients’ judgments. The part played by similarity between exemplar and recipient. European Journal of Communication, 14(2), 213–224. https://doi.org/10.1177/0267323199014002004

Bruter

(2004). On what citizens mean by feeling “European”: Perceptions of news, symbols and borderless-ness. Journal of Ethnic and Migration Studies, 30(1), 21–39. https://doi.org/10.1080/1369183032000170150

Cacciatore

M. A.

Scheufele

D. A.

Iyengar

(2016). The end of framing as we know it . . . and the future of media effects. Mass Communication and Society, 19(1), 7–23. https://doi.org/10.1080/15205436.2015.1068811

10.

Campbell

D. T.

(1965). Ethnocentric and other altruistic motives. In Levine

(Ed.), Nebraska symposium on motivation (pp. 283–311). University of Nebraska Press.

11.

Cao

(2008). Political comedy shows and knowledge about primary campaigns: The moderating effects of age and education. Mass Communication and Society, 11, 43–61. https://doi.org/10.1080/15205430701585028

12.

Chong

Druckman

J. N.

(2007a). Framing theory. Annual Review of Political Science, 10, 103–126. https://doi.org/10.1146/annurev.polisci.10.072805.103054

13.

Chong

Druckman

J. N.

(2007b). A theory of framing and opinion formation in competitive elite environments. Journal of Communication, 57(1), 99–118. https://doi.org/10.1111/j.1460-2466.2006.00331.x

14.

Cobb

M. D.

Kuklinski

J. H.

(1997). Changing minds: Political arguments and political persuasion. American Journal of Political Science, 41(1), 88–121.

15.

Costello

Hodson

(2011). Social dominance-based threat reactions to immigrants in need of assistance. European Journal of Social Psychology, 41(2), 220–231. https://doi.org/10.1002/ejsp.769

16.

Daschmann

Brosius

H.-B.

(1999). Can a single incident create an issue? Exemplars in German television magazine shows. Journalism & Mass Communication Quarterly, 76(1), 35–51. https://doi.org/10.1177/107769909907600104

17.

de Vreese

Boomgaarden

H. G

. (2006). Media effects on public opinion about the enlargement of the European Union. Journal of Common Market Studies, 44(2), 419–436. https://doi.org/10.1111/j.1468-5965.2006.00629.x

18.

de Vreese

Boomgaarden

H. G.

Semetko

H. A

. (2011). (In)direct framing effects: The effects of news media framing on public support for Turkish membership in the European Union. Communication Research, 38(2), 179–205. https://doi.org/10.1177/0093650210384934

19.

Dogan

Pelassy

(1984). How to compare nations: Strategies in comparative politics. Chatham House.

20.

Druckman

J. N.

Fien

Leeper

T. J.

(2012). A source of bias in public opinion stability. American Political Science Review, 106(2), 430–454. https://doi.org/10.1017/S0003055412000123

21.

Dustmann

Preston

I. P.

(2007). Racial and economic factors in attitudes to immigration. The B.E. Journal of Economic Analysis & Policy, 7(1), 1–39. https://doi.org/10.2202/1935-1682.1655

22.

Eberl

J.-M.

Meltzer

C. E.

Heidenreich

Herrero

Theorin

Lind

Berganza

Boomgaarden

H. G.

Schemer

Strömbäck

(2018). The European media discourse on immigration and its effects: A literature review. Annals of the International Communication Association, 42(3), 207–223. https://doi.org/10.1080/23808985.2018.1497452

23.

Entman

Matthes

Pellicano

(2009). Nature, sources and effects of news framing. In Wahl-Jorgensen

Hanitzsch

(Eds.), Handbook of journalism studies (pp. 175–190). Routledge.

24.

Eurostat. (2019a). https://ec.europa.eu/eurostat/statistics-explained/index.php/Gender_statistics

25.

Eurostat. (2019b). https://ec.europa.eu/eurostat/statistics-explained/index.php/Population_structure_and_ageing#The_share_of_elderly_people_continues_to_increase

26.

Eurostat. (2019c). https://ec.europa.eu/eurostat/statistics-explained/index.php?title=File:Share_of_the_population_by_educational_attainment_level_and_selected_age_groups,_2018_(%25).png

27.

Ford

(2011). Acceptable and unacceptable immigrants: How opposition to immigration in Britain is affected by migrants’ region of origin. Journal of Ethnic and Migration Studies, 37(7), 1017–1037. https://doi.org/10.1080/1369183X.2011.572423

28.

Franco

Malhotra

Simonovits

(2014). Publication bias in the social sciences: Unlocking the file drawer. Science, 345(6203), 1502–1505. https://doi.org/10.1126/science.1255484

29.

Gerber

A. S.

Malhotra

Drowling

C. M.

Doherty

(2010). Publication bias in two political behavior literatures. American Political Research, 38(4), 591–613. https://doi.org/10.1177/1532673X09350979

30.

González-Ferrer

Moreno-Fuentes

F. J.

(2017). Back to the suitcase? Emigration during the great recession in Spain. South European Society and Politics, 22(4), 447–471. https://doi.org/10.1080/13608746.2017.1413051

31.

Goodwin

Milazzo

(2017). Taking back control? Investigating the role of immigration in the 2016 vote for Brexit. The British Journal of Politics and International Relations, 19(3), 450–464. https://doi.org/10.1177/1369148117710799

32.

Gross

(2008). Framing persuasive appeals: Episodic and thematic framing, emotional response, policy options. Political Psychology, 29(2), 169–192. https://www.jstor.org/stable/20447111

33.

Hainmueller

Hiscox

M. J.

(2010). Attitudes toward highly skilled and low-skilled immigration: Evidence from a survey experiment. American Political Science Review, 104(1), 61–84. https://doi.org/10.1017/S0003055409990372

34.

Hainmueller

Hopkins

D. J.

(2014). Public attitudes toward immigration. Annual Review of Political Science, 17(1), 225–249. https://doi.org/10.1146/annurev-polisci-102512-194818

35.

Hakhverdian

van Elsas

van der Brug

Kuhl

(2013). Eurosceptisism and education: A longitudinal study of 12 EU member states, 1973-2010. European Union Politics, 14(4), 522–541. https://doi.org/10.1177/1465116513489779

36.

Hobolt

(2016). The Brexit vote: A divided nation, a divided continent. Journal of European Public Policy, 23(9), 1259–1277. https://doi.org/10.1080/13501763.2016.1225785

37.

Huber

G. A.

Lapinski

J. S.

(2006). The “race card” revisited: Assessing racial priming in policy contests. American Journal of Political Science, 50(2), 421–440. https://www.jstor.org/stable/3694281

38.

Ienciu

N. M.

Ienciu

I.-A.

(2015). Brain drain in central and eastern Europe: New insights on the role of public policy. Southeast European and Black Sea Studies, 15(3), 281–299. https://doi.org/10.1080/14683857.2015.1050799

39.

Igartua

J.-J.

Cheng

(2009). Moderating effect of group cue while processing news on immigration. Journal of Communication, 59(4), 726–749. https://doi.org/10.1111/j.1460-2466.2009.01454.x

40.

Igartua

J.-J.

Moral-Toranzo

Fernández

(2011). Cognitive, attitudinal, and emotional effects of news frame and group cues, on processing news about immigration. Journal of Media Psychology, 23(4), 174–185. https://doi.org/10.1027/1864-1105/a000050

41.

Iyengar

(1991). Is anyone responsible? How television frames political issues. The University of Chicago Press.

42.

Iyengar

(1996). Framing responsibility of political issues. The ANNALS of the American Academy of Political and Social Science, 546, 59–70.

43.

Karstens

(2019). How public discourse affects attitudes towards freedom of movement and Schengen. European Union Politics, 21, 43–63. https://doi.org/10.1177/1465116519874880

44.

Lahav

Courtemanche

. (2012). The ideological effects of framing threat on immigration and civil liberties. Political Behavior, 34(3), 477–505. https://doi.org/10.1007/s11109-011-9171-z

45.

Lecheler

de Vreese

(2018). News framing effects. Routledge.

46.

Maurer

(2014). Attitudinal effects in political communication. In Reinemann

(Ed.), Political communication (pp. 591–607). de Gruyter.

47.

Mazza

Soto

(2019). Considering intra-EU migration and countries’ net inflows. https://www.bruegel.org/2019/03/considering-intra-eu-migration-and-countries-net-inflows/

48.

Meeusen

Jacobs

(2017). Television news content of minority groups as an intergroup context indicator of differences between target-specific prejudices. Mass Communication and Society, 20(2), 213–240. https://doi.org/10.1080/15205436.2016.1233438

49.

Meltzer

C. E.

Eberl

J.-M.

Theorin

Heidenreich

Strömbäck

Boomgaarden

H. G.

Schemer

(2020). Media effects on policy preferences toward free movement: Evidence from five EU member states. Journal of Ethnic and Migration Studies. Advance online publication. https://doi.org/10.1080/1369183X.2020.1778454

50.

Montgomery

J. M.

Nyhan

Torres

(2018). How conditioning on posttreatment variables can ruin your experiment and what to do about it. American Journal of Political Science, 62(3), 760–755. https://doi.org/10.1111/ajps.12357

51.

Pardos-Prado

(2011). Framing attitudes towards immigrants in Europe: When competition does not matter. Journal of Ethnic and Migration Studies, 37(7), 999–1015. https://doi.org/10.1080/1369183X.2011.572421

52.

Pichler

(2009). Cosmopolitan Europe. European Societies, 11(1), 3–24. https://doi.org/10.1080/14616690802209697

53.

Pomerantz

E. M.

Chaiken

Tordesillas

R. S.

(1995). Attitude strength and resistance processes. Journal of Personality and Social Psychology, 69(3), 408–419.

54.

Potter

J. W.

(2012). Media effects. SAGE.

55.

Ruhs

(2017). Free movement in European Union: National institutions vs common policies? International Migration, 55, 22–38. https://doi.org/10.1111/imig.12398

56.

Schemer

(2012). The influence of news media on stereotypic attitudes toward immigrants in a political campaign. Journal of Communication, 62, 739–757. https://doi.org/10.1111/j.1460-2466.2012.01672.x

57.

Schemer

(2014). Media effects on racial attitudes: Evidence from a three-wave panel survey in a political campaign. International Journal of Public Opinion Research, 26(4), 531–542. https://doi.org/10.1093/ijpor/edt041

58.

Scheve

K. F.

Slaughter

M. J.

(2001). Labor market competition and individual preferences over immigration policy. The Review of Economics and Statistics, 83(1), 133–145. https://www.jstor.org/stable/2646696

59.

Schmuck

Matthes

(2015). How anti-immigrant right-wing populist advertisements affect young voters: Symbolic threats, economic threats and the moderating role of education. Journal of Ethnic and Migration Studies, 41(10), 1577–1599. https://doi.org/10.1080/1369183X.2014.981513

60.

Schmuck

Matthes

(2017). Effects of economic and symbolic threat appeals in right-wing populist advertising on anti-immigrant attitudes: The impact of textual and visual appeals. Political Communication, 34(4), 607–626. https://doi.org/10.1080/10584609.2017.1316807

61.

Schotte

Winkler

(2018). Why are the elderly more averse to immigration when they are more likely to benefit? Evidence across countries. International Migration Review, 52(4), 1250–1282. https://doi.org/10.1177/0197918318767927

62.

Shehata

Falasca

(2014). Priming effects during the financial crisis: Accessibility and applicability mechanisms behind government approval. European Political Science Review, 6(4), 597–620. https://doi.org/10.1017/S1755773913000258

63.

Slothuus

de Vreese

(2010). Political parties, motivated reasoning, and issue framing effects. The Journal of Politics, 72(3), 630–645. https://doi.org/10.1017/s002238161000006x

64.

Springer

S. A.

Harwood

(2015). The influence of episodic and thematic frames on policy and group attitudes: Mediational analysis. Human Communication Research, 41(2), 226–244. https://doi.org/10.1111/hcre.12045

65.

Stephan

W. G.

Stephan

C. W.

(2000). An integrated threat theory of prejudice. In Ostkamp

(Ed.), Reducing prejudice and discrimination (pp. 23–45). Lawrence Erlbaum.

66.

Stephan

W. G.

Ybarra

Rios Morrisson

(2009). Intergroup threat theory. In Nelson

T. D.

(Ed.), Handbook of prejudice, stereotyping, and discrimination (pp. 43–59). Psychology Press.

67.

Strömbäck

Esser

(2015). Making sense of mediatized politics: Theoretical and empirical perspectives. Routledge.

68.

Taber

C. S.

Lodge

(2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50(3), 755–769.

69.

Tesler

(2015). Priming predispositions and changing policy positions: An account of when mass opinion is primed or changed. American Journal of Political Science, 59(4), 806–824. https://doi.org/10.1111/ajps.12157

70.

Theorin

Meltzer

Eberl

J.-M.

Lind

Galyga

Heidenreich

Strömbäck

Schemer

Boomgaarden

H. G.

(2020). REMINDER: Online experiment on migration and mobility attitudes 2019 (SUF edition) [Data set and documentation]. AUSSDA Dataverse. https://doi.org/10.11587/ZVXGS9

71.

Theorin

Strömbäck

(2020). Some media matter more than other: Investigating media effects on attitudes toward and perceptions of immigration in Sweden. International Migration Review, 54(4), 1238–1264. https://doi.org/10.1177/0197918319893292

72.

Valentino

N. A.

Soroka

S. N.

Iyengar

Aalberg

Duch

Fraile

Kobayashi

(2017). Economic and cultural drivers of immigrant support worldwide. British Journal of Political Science, 11(1), 1–26. https://doi.org/10.1017/S000712341700031X

73.

Valkenburg

P. M.

Peter

(2013). The differential susceptibility to media effects model. Journal of Communication, 63(2), 221–243. https://doi.org/10.1111/jcom.12024

74.

Vasilopoulou

Talving

(2019). Opportunity or threat? Public attitudes towards EU freedom of movement. Journal of European Public Policy, 26(6), 805–823. https://doi.org/10.1080/13501763.2018.1497075

75.

Vergeer

Lubbers

Scheepers

(2000). Exposure to newspapers and attitudes toward ethnic minorities: A longitudinal analysis. Howard Journal of Communications, 11(2), 127–143. https://doi.org/10.1080/106461700246661

76.

Visser

P. S.

Krosnick

J. A.

(1998). Development of attitude strength over the life cycle: Surge and decline. Journal of Personality and Social Psychology, 75(6), 1389–1410. https://doi.org/10.1037/0022-3514.75.6.1389

77.

Vliegenthart

Schuck

A. R. T.

Boomgaarden

H. G.

de Vreese

C. H.

(2008). News coverage and support for European integration, 1990-2006. International Journal of Public Opinion Research, 20(4), 415–439. https://doi.org/10.1093/ijpor/edn044

78.

Zaller

(1992). The nature and origins of mass opinion. Cambridge University Press.

79.

Zillmann

(2002). Exemplification theory of media influence. In Bryant

Zillmann

(Eds.), Media effects: Advances in theory and research (pp. 19–41). Lawrence Erlbaum.

80.

Zillmann

Gibson

S. R.

Sundar

Perkins

J. W.

(1996). Effects of exemplification in news reports on the perception of social issues. Journalism & Mass Communication Quarterly, 73(2), 427–444. https://doi.org/10.1177/107769909607300213

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

1.55 MB