“ They Did It”: The Effects of Emotionalized Blame Attribution in Populist Communication

Abstract

How can we explain the persuasiveness of populist messages, and who are most susceptible to their effects? These questions remain largely unanswered in extant research. This study argues that populist messages are characterized by assigning blame to elites in an emotionalized way. As previous research pointed at the guiding influence of blame attributions and emotions on political attitudes, these message characteristics may explain populism’s persuasiveness. An experiment using a national sample (N = 721) was conducted to provide insights into the effects of and mechanisms underlying populist blame attribution with regard to the European and national levels of governance. The results show that emotionalized blame attributions influence both blame perceptions and populist attitudes. Identity attachment moderates these effects: Emotionalized blame attributions have the strongest effects for citizens with weaker identity attachments. These insights allow us to understand how populist messages affect which citizens.

Keywords

political communication (media) populism responsibility attribution populist blame attribution populist attitudes

Already more than a decade ago, Mudde (2004) spoke of a populist zeitgeist in Europe. If anything, this zeitgeist has become even more pervasive in recent years. In Greece, for example, the left-wing anti-establishment party Syriza has made it into the government. Populism also prevails outside of Europe. The Tea Party in the United States, for example, is considered to be a platform for conservative populist discontent (Barstow, 2010). In the midst of the dissemination of the populist zeitgeist, a growing body of literature points to the pivotal role of communication in delivering the populist message to the people (e.g., Krämer, 2014; Mudde, 2004). Mudde even argues that the populist zeitgeist is partially caused by the media’s receptivity to the populist discourse.

The core of populism revolves around the moral distinction between the good people and the culprit elites, who are unable or unwilling to represent the people’s will. This idea can be expressed by different actors, such as politicians, the media, or citizens. The media can be populist by framing issues in terms of the opposition between law-abiding citizens and culprit politicians. If citizens perceive an antagonism between the good people and the corrupt elites, their interpretation of societal issues can also be regarded as populist.

Populist messages are argued to be highly persuasive as they respond to the ordinary people’s hopes and fears while formulating easy solutions to important societal problems (Hawkins, 2010; Mudde, 2004; Rooduijn, 2014). However, previous research failed to demonstrate what specific elements of populist media messages contribute to their persuasiveness. Vasilopoulou, Halikiopoulou, and Exadaktylos (2013) do point to one key distinguishing feature of the communication tactic of populists: They attribute more blame to the government and the European Union (EU) than mainstream politicians. By highlighting the purity of the people and by referring to the establishment as culprit, populism is inherently about attributing blame to others while absolving the people of responsibility. Populist messages attribute blame using a highly emotionalized style, emphasizing anger and fear toward threatening political elites (Fieschi & Heywood, 2004; Mudde, 2004; Ruzza & Fella, 2011). Reasoned from this perspective, the populist core idea distinguishes itself from mainstream politics by emotionally blaming elites (e.g., “Europe” or national governments) for causing the problems of the heartland (Stanley, 2008; Vasilopoulou et al., 2013).

Previous research on attributions of responsibility—a concept strongly related to populist blame attribution—indicates that citizens’ political attitudes are affected by messages that emphasize who should be blamed for causing political problems (Hobolt & Tilley, 2014). Moreover, it is shown that the emotional style of blame attributions bolsters their persuasiveness (Brader, 2005). Despite the fact that prior research implicitly hinted at the persuasiveness of populist blame attributions, no empirical studies on its effects and underlying mechanisms have been conducted. Therefore, the central aim of this study is to provide insight into how emotionalized blame attribution—the core element of populist messages—influences citizens’ blame perceptions and populist attitudes.

We conducted a 3 × 2 between-subjects online survey experiment (N = 721) to assess how citizens’ blame perceptions and populist attitudes toward the elites of the national government and the EU are affected by emotionalized attributions of blame. Doing so, this study responds to calls by scholars who have emphasized that the effects of media populism on the receiver side of the populist discourse should be studied more thoroughly (Jagers & Walgrave, 2007; Krämer, 2014; Mazzoleni, 2008). In general, we found that emotionalized blame attributions guide both blame perceptions and populist attitudes. Identification with the nation or Europe moderated these effects. These findings indicate that emotionalized blame attribution provides a relevant framework for understanding the persuasiveness of populist communication, which allows us to explain what message characteristics affect the populist attitudes of which citizens.

Populist Communication as Emotionalized Blame Attribution

Citizens are assumed to credit the government for successes and blame it for failures. This process, which is crucial for democratic functioning, is called attribution of responsibility (Gomez & Wilson, 2008; Malhotra & Kuo, 2008; Tilley & Hobolt, 2011). In this article, we focus on causal attributions of responsibility that attribute negative qualities to the elites on the national and European levels of governance drawing on the emotions of anger and fear. We therefore conceptualize these causal attributions of responsibility as emotionalized blame attributions to elites. But how is this blame game related to populism?

Although many scholars still disagree on how to precisely define populism, consensus exists that populism entails the construction of a blameless in-group opposed to a culprit out-group (Canovan, 1999; Mudde, 2004; Taggart, 2000). As the moral opposition between the pure people against the corrupt elites is the lowest common denominator central to all types of populism, we take this populist core as a point of departure throughout this paper (Rooduijn, 2014). This core consists of two main components: (a) the perception that politicians should, but are failing to, represent the will of the ordinary people and (b) the perceived antagonism between the good people and the evil elites (Jagers & Walgrave, 2007).

Populism can be connected to responsibility attribution. Populism always portrays the people as a homogeneous in-group belonging to the imagined community of the heartland (Taggart, 2000). This heartland is in a severe state of crisis because the elites (e.g., the EU and the government) failed to represent the will of the people (Canovan, 1999). Hence, the in-group is threatened by the “corrupt elite,” the homogeneous out-group constructed in opposition to the people (Laclau, 1977; Mudde, 2004). As the people are silenced by corrupt politicians who are blind to see the real problems of the nation, the people cannot help their heartland being in a state of crisis: The corrupt elites are held responsible for causing the crisis of the heartland (Taggart, 2000). Attributing responsibility for negative outcomes—blame—to the corrupt elites for causing the people’s problems is thus inherently populist (Jagers & Walgrave, 2007).

In general, populist communication emphasizes the opposition of the people to representative democracy (e.g., Canovan, 1999). In Western Europe, this entails attributing blame to national as well as European levels of governance. For this reason, we focus on the EU and the national government as the culprit out-groups (Jagers & Walgrave, 2007; Taggart, 2000). An example of such blame-shifting rhetoric was articulated by the United Kingdom Independence Party (UKIP) leader Nigel Farage in an online British newspaper: “Unless we leave the EU, a huge surge in population growth is unavoidable” (Farage, 2015). In this message, the EU is blamed for causing a salient problem of the in-group of the British nation.

The Role of the Media in Framing Populist Blame Attributions

The media play a crucial role in disseminating populist messages to the people (Krämer, 2014; Mazzoleni, 2008; Muis & Scholte, 2013). When referring to the relationship between the media and populism, a distinction between populism by the media and populism intended for the media can be made (Bos & Brants, 2014). The latter form of relationship concerns the media’s receptivity to populist ideas, whereas the former identified relationship taps into the concept of media populism (e.g., Krämer, 2014; Mazzoleni, 2008).

Media populism can be defined as the adaptation of elements of populist ideas (e.g., construction of pure people versus corrupt elites) and style (e.g., emotionalized) by the media themselves (Krämer, 2014). In line with the concept of media populism, the media may actively use emotional blame attribution as a framework for the coverage of political issues. Using the populist core idea, the media emphasize the distinction between the culprit elites and the blameless people. Moreover, they communicate this message in an emotional style that reflects hostility toward these elites, for example, by emphasizing the outrage of the common people toward the corrupt government or by stressing the people’s fear of the threatening EU. Emotionalized blame attribution is thus not only confined to populist actors, but it can also be part of the content of populist messages. The following quotes of messages posted on the Tea Party’s website illustrate such content: “Liz Cheney blasted Barack Obama’s disastrous foreign policy” and “Barack Obama is a dangerous man and he is punch-drunk on power. Bash Obama on Facebook? Be afraid, very afraid” (“Obama Has Proceeded Over Last 7 Years,” 2015). In these messages, the U.S. president is not only personally blamed for the government’s failing policy, the words “blasted,” “disastrous,” and “afraid” indicate that blame is attributed using an emotional style.

The media can create effects of populism through framing, which entails the reconstruction of social reality in meaningful patterns of interpretation (Scheufele, 1999). In Entman’s (1993) frequently cited definition of framing, media frames are conceptualized as consisting of four frame-elements: a problem definition, a causal interpretation, a moral evaluation, and/or a treatment recommendation. As populist messages emphasize who is causally responsible for the defined problem while morally evaluating the people’s will as “good” and the elites’ influence as “evil,” the framing of populist messages connects most saliently to the first three frame-elements.

The framing approach has previously been applied to research on both populism and attributions of responsibility. Assigning responsibility, which taps into the frame-element of causal interpretation, plays a central role in media framing as it affects citizens’ interpretation of political issues (Iyengar, 1991; Kühne, Weber, & Sommer, 2015). Reasoned from framing research on populism, the central populist frame has previously been defined as “us versus them” (e.g., Caiani & Della Porta, 2011). This populist frame taps into the causal interpretation as well as the moral evaluation of issues as the in-group is perceived of as morally good and absolved of responsibility while “they” are evil and causally responsible. In line with this, Jagers and Walgrave (2007) argue that the populist master frame concerns the distinction between the blameless people and the corrupt elites. Synthesizing insights into the framing of populism and responsibility, we argue that the central populist frame should be perceived as a “blame the corrupt elites who are opposed to the people frame.” But what are the potential effects of these populist “blame frames”?

As a consequence of exposure to messages that emphasize the divide between the people and the elites, citizens may interpret society in binary “us” against “them” oppositions themselves as well (Krämer, 2014). These populist interpretations are frequently expressed on social media, for example: “The prime minister needs to go and we need out of EU now.” By activating such interpretations among citizens, populist messages contribute to “media based othering.” This process can further be explained by psychological theories on stereotyping. Populist blame frames make negative stereotypes of the EU and the national government chronically accessible to the people (e.g., Dixon, 2008). Populist messages that accuse corrupt politicians for not providing enough jobs for ordinary hard-working citizens may, for example, strengthen citizens’ perception that they are not responsible for their own situation. This negative stereotype of the elites as culprit and the people as blameless victims becomes accessible when citizens think about politics.

As political issues are difficult to comprehend and citizens frequently lack factual information on who is responsible for political issues at different levels of governance (e.g., Arceneaux, 2006; Cutler, 2004), citizens are expected to use the stereotypes provided in populist messages when forming an opinion on the political elites in the EU and the national government. As attribution of responsibility provides a powerful psychological cue for the formation of favorable attitudes toward the in-group and hostile attitudes toward the out-group, citizens’ blame perceptions and populist attitudes are expected to be guided by blame frames (Hobolt & Tilley, 2014; Krämer, 2014). By marking the moral distinction between “us” and “them,” populist blame frames are thus expected to affect citizens’ blame perceptions and populist attitudes. Against this backdrop, we hypothesize the following:

Hypothesis 1 (H1): Blame attributions in populist communication guide citizens’ blame perceptions and populist attitudes.

Social Identity: The Perceptual Screen Moderating the Effects of Blame Attribution

Our central argument is that blame attribution is at the core of populist political communication. Hypothesis 1 suggests that citizens—ceteris paribus—follow suit when either the national government or the EU is blamed. However, populist blame attribution may not be effective for all citizens. Krämer (2014) expects that citizens who do not share the worldview articulated by populist media will respond to populist communication with reactance. Moreover, Lenz (2009) showed that individuals accept the ideas of parties they identify themselves with and reject the ideas of parties they oppose. In studies on attributions of responsibility, it is demonstrated that government partisans are less likely to accept blame attribution to the government than supporters of the opposition (Tilley & Hobolt, 2011). Likewise, citizens’ feelings of closeness to national or European identity may restrain them from forming negative attitudes toward the national government or the EU. But what is the underlying process that makes citizens resistant to persuasion by the populist blame game?

In social psychology, the process underlying populist blame attribution, in-group versus out-group construction, is called social categorization (Aronson, Wilson, & Akert, 2007). This process results in out-group homogeneity and in-group serving bias. In-group bias is defined as the experience of positive feelings for the in-group, in this case the Dutch nation-state or the EU, and negative feelings for the out-group constructed as significantly different from the EU or the nation. Out-group homogeneity means that people belonging to the out-group are perceived as more similar to each other than they actually are (Aronson et al., 2007). We call these in-group and out-group biases the “perceptual screen.”

Social identity theory explains how the perceptual screen mechanism influences attitudes toward the in-group and out-group (Tajfel, 1978). This theory argues that the experience of belonging to the in-group forms a crucial part of people’s self-concept. As people want to maintain a positive self-concept, they are biased in their judgments and attribute negative qualities (e.g., blame) to the out-group that is perceived as significantly different (Gordon & Arian, 2001; Tajfel, 1978). For a consistent positive self-concept, the in-group is absolved of blame (McLaren, 2007; Sniderman, Peri, de Figueiredo, & Piazza, 2000).

In line with this mechanism, people are expected to only accept blame attributed on the national level when they do not feel close to their nation. When people do feel connected to their nation, accepting frames that attribute blame on the national level is inconsistent with their positive self-concept. Likewise, we expect that people will only blame the EU when they are not attached to European identity. These effects are explained by in-group serving bias, functioning as a frame of reference or a perceptual screen when citizens assign responsibility (Tilley & Hobolt, 2011). Attachment to identity may thus be key in understanding the conditionality of populist communication’s effects. In this study’s context, people who identify strongly with Dutch culture and citizenry should not be persuaded by populist messages that blame “their” government. If people feel strongly connected to European identity, the EU is part of their in-group and therefore absolved of causal responsibility for negative outcomes.

In other words,

Hypothesis 2 (H2): Identity attachment functions as a perceptual screen when citizens construct blame perceptions and populist attitudes in response to populist political communication.

Specifically,

Hypothesis 2a (H2a): Citizens who feel attached to national identity are less likely to accept frames attributing blame to the national government than citizens who do not feel attached to national identity.

Hypothesis 2b (H2b): Citizens who feel attached to European identity are less likely to accept frames attributing blame to the EU than citizens who do not feel attached to European identity.

The Role of Anger and Fear in the Populist Blame-Game

Previous research indicated that emotionally charged information affects citizens’ opinions in a different way than information that is presented without references to emotions (Gadarian, 2010). Therefore, it is important to study how the effects of populist blame attribution depend on the use of different negative emotions central in populism.

Populists attribute blame using an emotional communication style (Fieschi & Heywood, 2004; Ruzza & Fella, 2011). By emphasizing that the enemies (e.g., the corrupt elites of the EU and the national government) are creeping upon the heartland (Finlay, 2007), the emotional style of populist messages instills a sense of threat on the people. This threat is communicated by using the negative emotions of anger and fear, for example, by emphasizing how ordinary citizens fear the EU’s impact on their insecure future or by stressing outrage toward the government’s failing policy. In research on responsibility attributions, expressions of anger and fear are found to affect blame perceptions in different ways (e.g., Nabi, 2003).

Populist communication draws on anger to emphasize that the culprit elites are blocking the goals of the people (Grant & Brown, 1995; Ruzza & Fella, 2011). Fear is used to highlight uncertainty about the threatening future of the heartland, which is in a state of crisis because the corrupt elites failed to represent the people (Mols & Jetten, 2014). The negative emotions of anger and fear thus play different roles in the populist blame game. As these negative emotions are central in populist constructions of the elites, we will investigate how anger and fear as emotional styles affect citizens’ responses to populist blame attribution messages.

Research into the role of discrete emotions in framing often draws on appraisal theory. This theory describes how emotions are experienced as a consequence of a person’s subjective interpretation of a situation (Lerner & Keltner, 2001). This interpretation is referred to as an “appraisal tendency” or an “appraisal pattern.” According to appraisal theory, specific emotions elicit specific appraisal patterns, which in turn influence how information is processed (Nabi, 2003). Crucially, anger and fear as discrete emotional styles have different effects on how citizens process information on causal attributions of responsibility for negative outcomes, or blame (Han, Lerner, & Keltner, 2007).

Specifically, anger’s appraisal pattern stimulates heuristic processing, whereas fear’s appraisal pattern stimulates systematic processing (Kim & Cameron, 2011). Fear’s appraisal tendencies of uncertainty and uncontrollability construct the perception of a threat that needs to be dealt with. To resolve feelings of uncertainty and to avert the threat, new information in the environment is processed systematically (e.g., Major, 2011). As fear stimulates systematic processing of new information, fear is expected to result in a tendency to accept populist blame attributions (e.g., Brader, 2005). This expectation is in line with the findings of Gadarian (2010), who found that fear-inducing cues increased the likelihood of a threatening message’s acceptance.

In contrast to fear, anger’s appraisal pattern creates the perception of certainty and controllability. As feelings of certainty and control do not motivate people to search for new information, anger stimulates heuristic processing. This results in citizens’ dependency on existing attitudes (Lerner & Keltner, 2001; Leventhal & Scherer, 1987). Reasoned from appraisal theory, we hypothesize the following:

Hypothesis 3a (H3a): The emotionalized style of fear will lead to a stronger tendency to accept populist blame attribution than anger.

In addition, we expect that the effects of anger and fear will be contingent upon the experienced level of identity attachment. As we already predicted that fear has a stronger impact than anger, and weaker attached citizens are most susceptible to persuasion, we further hypothesize the following:

Hypothesis 3b (H3b): The effects of the emotional style of the message are moderated by identity attachment, so that specifically at lower levels of identity attachment, fear will lead to stronger blame perceptions and populist attitudes than anger.

At higher levels of identity attachment, the emotional style of the message should not affect blame perceptions and populist attitudes.

Finally, reasoned from the perceptual screen mechanism, the acceptance of blame frames should differ at different levels of identity attachment. Moreover, appraisal theory predicts that fear leads to a stronger tendency to accept attributions of responsibility than anger. Synthesizing these predictions, we raise the following research question (RQ1):

Research Question 1 (RQ1): Is the acceptance of the fear blame frame highest among lower levels of social identity?

Method

Design

To test how emotionalized attributions of blame affect blame perceptions and populist attitudes, we conducted a 3 (Causal responsibility attribution: the EU vs. the national government vs. no-responsibility attribution) × 2 (Emotionalized style: anger vs. fear) between-subjects factorial design with control group. Respondents were randomly assigned to one of the six experimental conditions or the control group (see Table 1, for all conditions).

Table 1.

3 × 2 Between-Subjects Factorial Design With Control Group.

Emotional style blame attribution	Anger	Fear
The EU	Group 1: The EU is attributed blame; anger is highlighted	Group 2: The EU is attributed blame; fear is highlighted
The Dutch government	Group 3: The Dutch government is attributed blame; anger is highlighted	Group 4: The Dutch government is attributed blame; fear is highlighted
No-blame attribution	Group 5: No blame is attributed; anger is highlighted	Group 6: No blame is attributed; fear is highlighted
Control group	No-blame attribution and no emotionalized style

Sample

This study is based on a diverse sample of Dutch citizens recruited by Research Now. A filter question was used to assess whether participants were able to adequately respond to a question about a short text.¹ The final sample consisted of 721 participants who complied with the instruction.² The mean age of the participants was 47.24 years (SD = 16.62), and 52.9% were female. In all, 46.6% of the sample was lower educated, 42.3% was higher educated, and 13.9% had a moderate level of education. Informed by a pilot study, we expected that 100 participants per condition would result in a desired power of 0.80. The actual observed power of the analyses to detect differences between experimental conditions was 0.79 (α = .05).

Procedure

The experiment was conducted online. Participants first completed the procedure of informed consent. Upon agreement, participants completed the filter question. Only if they were not screened out, they completed a pretest asking for demographics, the items for moderating variables and control variables. Next, participants were randomly allocated to one of the experimental conditions and read an online newspaper article. After reading this article, participants completed a posttest questionnaire measuring the dependent variables. At the end of the questionnaire, manipulation check items for causal responsibility attributions and emotionalized style were assessed. On average, participants completed the survey in 15.27 minutes, of which 65.70 seconds were spent on reading the newspaper article. Upon completion, participants received a financial incentive from the research agency.

Independent Variables and Stimulus Materials

The stimuli consisted of a negatively valenced online newspaper article on the worsening Labour market situation. This issue was chosen as it has both a national and an EU political dimension (Kriesi et al., 2008). As this issue is salient in Dutch public and political debates, it provides an externally valid case for which politicians and citizens evaluate causal responsibility all the time. The article was framed in seven different ways depending on the level of the independent variables emotionalized style and blame attributions. All versions of the article are included in Appendix A.

Emotionalized style was manipulated in terms of appraisal patterns and emotion words that indicate anger and fear (e.g., Kühne, 2014; Nabi, 2003). In the fear conditions, pessimism, uncontrollability, and responsibility attributions directed at institutions related to the out-group were emphasized. Protection against rather than punishment of responsible actors was emphasized. The emotion words “tension,” “fear,” “afraid,” and “pessimistic” were used as indicators of fear (see also Nabi, 2003). In the anger conditions, controllability, certainty, and causal responsibility attributions to concrete actors were emphasized. Approach behavior was emphasized by highlighting the need to punish the specific actors responsible for the worsening Labour market situation. The emotion words “angry,” “outraged,” “punish,” and “frustrated” were used to indicate the discrete emotion of anger. We thus used four emotion-indication words in each emotionalized style condition.

To enhance external validity, the stimuli were based on four existing newspaper articles retrieved from online versions of three Dutch newspapers (de Volkskrant, de Telegraaf, NRC.next). The constructed articles ranged between 136 and 166 words in length and had the same number of paragraphs. The layout, style, language, sources, and content of the stimuli matched existing online newspaper articles. In all versions of the newspaper article, the storyline was identical and focused on how the Labour market situation has worsened over the last few years. The source, statistics, and references to the in-group of Dutch citizens were held constant between all experimental conditions. In each article, only one source was quoted: the governmental organization that deals with unemployment benefits (the Executive Institute for Employees’ Insurances). In all articles, four indicators of blame attribution were used and presented in a similar way. All in all, we ensured that the wording of the stimuli only differed on the independent variables manipulated in this study.

Manipulation Checks

A pilot test among a convenience sample (N = 117) indicated that the manipulations were successful and that the stimuli affected perceptions of blame and emotional styles in the predicted direction. The manipulation check items used in the main study asked participants to remember the causes of the worsening Labour market situation mentioned in the newspaper article. The manipulation of causal responsibility attribution was successful for both blame attributed to the EU (F(2, 707) = 75.40, p < .001) and the national government (F(2, 709) = 49.44, p < .001). The manipulation of emotional style succeeded as well (F(2, 713) = 15.01, p < .001).

Measures

Unless explicitly stated otherwise, all items were measured on a 7-point scale (1 = completely disagree, 7 = completely agree). All items are included in their exact wording in Appendix B.

Citizens’ perceptions of blame

The key dependent variable was measured in two different ways. First, similar to Iyengar’s (1991) measure of responsibility attribution, perceptions of blame were measured with an open-ended question. Just like Iyengar asked participants to indicate what the most important causes of the issue were, we posed the following question: Can you describe whom or what you feel is most responsible for causing this situation? The responses to this question were recoded into four categories (1 = blame assigned to Dutch government, 2 = blame assigned to the EU, 3 = blame assigned to others, 4 = blame assigned to both the EU and national government). Intercoder reliability was assessed for a sample of 141 (19.6%) randomly selected open-ended questions coded by two independent coders who were trained by a detailed coding procedure that explained each of the four categories in detail. Krippendorff’s alpha was .86.

Second, participants were presented with 19 different “candidates for responsibility” (Gomez & Wilson, 2008). These different actors, organizations, political elites, and other out-groups appeared in a random order. Participants were asked to what extent they believed each was responsible for the worsening Labour market situation on a 7-point scale (1 = completely responsible, 7 = not at all responsible).

Populist attitudes

Following definitions by Mudde (2004) and Jagers and Walgrave (2007), populism consists of two core components: the (failed) representation of the ordinary people and the moral antagonism between the good people and the evil elites. Confirmatory Factor Analysis (CFA) was used to test whether the data fitted this two-factor measurement model (items derived from Akkerman, Mudde, & Zaslove, 2014; Hawkins, Riding, & Mudde, 2012). The model fitted the data well (χ²(5) = 10.85, p = .054; root mean square error of approximation [RMSEA] = 0.023, 90% confidence intervals [CI] = [0.00, 0.04]; comparative fit index [CFI] = 0.99). The correlation between the factors was .58. To further test for discriminant validity, we constrained the correlation between the two factors to 1.00, which resulted in a significant decline in model fit (∆χ² = 30.06, p < .001). This indicates that although both factors were related, they correlated too weakly to be merged into a one-dimensional populist attitudes scale. Two 7-point scales were constructed: Representation (M = 4.81, SD = 1.19, Cronbach’s α = .76) and Antagonism (M = 4.04, SD = 1.19, Cronbach’s α = .58). Higher scores on both scales indicate stronger populist attitudes on the corresponding dimension.

The items for the two dimensions of populist attitudes are listed in Appendix B. The items measuring the representation scale tap into participants’ perception that politicians should respond to the lifeworld of ordinary citizens by listening to their concerns, by understanding the problems they are facing, and by following their will. The essence of this scale thus describes the ways in which politicians, as representatives of the people, should be responsive to the problems experienced by the people (e.g., Albertazzi & McDonnell, 2008). The items of the antagonism scale tap into a perceived divide between the “good” ordinary people and the “bad” politicians. This scale thus vertically constructs political elites as the populist “other” (e.g., Hawkins, 2010; Mudde, 2004).

Moderators: Identity Attachment to the Netherlands and Europe

We used two three-item scales to measure social identity attachment. The items were based on measures used by Lubbers (2008) and Boomgaarden, Schuck, Elenbaas, and de Vreese (2011). We constructed a scale for Dutch identity attachment (M = 5.43, SD = 1.26, Cronbach’s α = .92) and a scale for European identity attachment (M = 3.84, SD = 1.49, Cronbach’s α = .86). Higher scores on the 7-point scales indicate a stronger identity attachment.

Control Variables

Our design allowed us to assure random assignment over experimental conditions, and we ensured that assignment to specific experimental conditions did not result in differential attrition (Mutz & Pemantle, 2011). For illustrative purposes, we performed a between-conditions randomization check on the control variables age, gender, level of education, news exposure, political efficacy, political distrust/cynicism, voting behavior, and attitudes toward the Labour market situation. We found no significant differences between experimental conditions regarding these variables.³

Analysis

Table B1 in Appendix B shows descriptive statistics of the main dependent variables for all experimental conditions. To test the hypotheses, logistic regression analysis and multivariate analyses of covariance (MANCOVAs)⁴ were conducted to assess how different levels of emotionalized blame attributions affected citizens’ blame perceptions and populist attitudes. In addition, multiple linear regression was used to assess how identity attachment moderated the effects of emotionalized style on out-group perceptions.

Results

Direct Effects of Populist Blame Attributions

The direct effects of populist attributions of blame are graphically depicted in Figure 1. First, we conducted a logistic regression analysis to assess how populist blame attributions affected open-ended blame perceptions. Blame attribution significantly affected open-ended blame perceptions toward both the Dutch government (b = 1.70, SE = 0.18, p < .001) and the EU (b = 3.05, SE = 0.28, p < .001) in the hypothesized direction. The odds ratio for the governmental blame attribution coefficient was 5.48 (95% CI = [3.86, 7.79]), which indicates that citizens in the governmental blame conditions were 5.48 times more likely to blame the government than citizens in the no-blame or EU-blame conditions. The odds ratio for the EU blame attribution coefficient was 21.13 (95% CI = [12.10, 36.90]), which indicates that citizens in the EU blame conditions were 21.13 times more likely to blame the EU than citizens in the no-blame attribution or governmental blame attribution conditions. The answers to the closed-ended questions only provide support for a direct effect of populist blame attribution on blame perceptions toward the EU (F(2, 696) = 8.53, p < .001, partial η² = 0.02). The effect again pointed in the hypothesized direction (see Table 2 for mean score differences between experimental conditions).

Figure 1.

Direct effects of populist blame attributions on dependent variables.

Table 2.

Scores on Dependent Variables for Different Blame Attribution Conditions.

	Experimental condition			Direct effects: F, Df (2, 696)	Partial η²
	No-blame attribution	EU blame attribution	Government blame attribution	Direct effects: F, Df (2, 696)	Partial η²
EU blame perceptions	4.39_a (1.28)	4.78_b (1.23)	4.33_c (1.31)	8.53**	0.02
Government blame perceptions	4.69_a (1.31)	4.86_a (1.23)	4.78_a (1.33)	0.18
Pop 1: Representation	4.63_a (1.15)	4.90_b (1.07)	4.97_b (1.12)	5.32**	0.02
Pop 2: Antagonism	3.96_a (1.04)	4.15_a (1.10)	4.07_a (1.18)	0.62

Note. Standard deviations are reported in parentheses to the right of means. Means with differing subscripts within the rows differ significantly at the p < .05 level based on independent samples t-test.

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

Of the two populist attitudes, only the representation dimension was directly affected by populist attributions of blame. Specifically, citizens exposed to attributions of responsibility to the EU or the national government were more inclined to believe politicians failed to represent the people’s will than citizens exposed to no-responsibility attributions (see Table 2 for mean differences).

Overall, the results offer partial support for Hypothesis 1. As expected, populist blame attributions were taken over by citizens but only affected both open-ended and closed-ended measures of blame when the EU was attributed responsibility. Moreover, only the populist representation attitude was directly affected by populist blame attributions.

The Perceptual Screen of Identity Attachment

The results indicate that identity attachment functions as a perceptual screen when citizens respond to populist blame attributions. We found a significant two-way interaction effect of blame attribution and Dutch identity attachment on citizens’ governmental blame perceptions: F(2, 670) = 5.38, p = .005, partial η² = 0.02. As shown in Table 3, citizens experiencing a weaker attachment to national identity accepted blame frames that attributed responsibility to the Dutch government. In contrast, citizens experiencing a stronger attachment to national identity were not persuaded by populist blame frames (see Table 3 for mean differences between experimental conditions). These findings offer support for H2a.

Table 3.

Effects of Emotionalized Blame Attributions on Blame Perceptions for Different Levels of Identity Attachment.

Dependent variable	Identity attachment level	Experimental conditions									Three-way interaction effect F, Df (2, 681)	Partial η²
		No-blame attribution			EU blame attribution			Government blame attribution
		Anger	Fear	Total	Anger	Fear	Total	Anger	Fear	Total
Perceptions EU blame	Weaker EU-identity	4.66_a,x	4.15_b,x	4.44_c,x	4.90_a,x	5.02_d,x	4.95_e,x	4.80_a,x	4.53_a,x	4.67_c,x	3.07**	0.03
	Weaker EU-identity	(1.35)	(1.34)	(1.37)	(1.07)	(1.46)	(1.25)	(1.42)	(1.43)	(1.43)
	Stronger EU- identity	4.36_a,x	4.50_b,x	4.34_c,x	4.50_a,x	4.79_b,x	4.66_d,x	4.01_a,y	4.12_a,x	4.07_c,y
	Stronger EU- identity	(1.10)	(1.24)	(1.21)	(1.20)	(1.20)	(1.20)	(1.26)	(1.02)	(1.14)
	Total	4.46_a	4.33_b	4.36_c	4.69_a	4.89_d,x	4.79_e	4.36_a	4.27_a	4.31_c
	Total	(1.22)	(1.30)	(1.28)	(1.16)	(1.28)	(1.22)	(1.37)	(1.24)	(1.31)
Perceptions Government blame	Weaker national identity	4.77_a,x	4.02_b,x	4.28_c,x	5.21_a,x	5.56_d,x	5.37_e,x	5.35_a,x	3.32_b,x	4.92_c,z	2.14*	0.02
	Weaker national identity	(1.48)	(1.68)	(1.55)	(1.50)	(1.05)	(1.29)	(1.39)	(1.50)	(1.40)
	Stronger national identity	4.99_a,x	4.79_b,x	4.74_c,y	4.76_a,x	4.86_b,x	4.81_c,y	4.74_a,x	4.82_a,y	4.78_c,x
	Stronger national identity	(1.11)	(1.33)	(1.28)	(1.22)	(1.21)	(1.21)	(1.39)	(1.22)	(1.30)
	Total	4.93_a	4.72_b	4.67_c	4.79_a	4.92_b	4.85_c	4.81_a	4.73_a	4.77_c
	Total	(1.15)	(1.34)	(1.30)	(1.26)	(1.21)	(1.21)	(1.38)	(1.27)	(1.33)

Note. Standard deviations are reported in parentheses below means. Means with differing first subscripts (a through e) within the rows and within emotionalized style differ significantly at the p < .05 level based on independent samples t-test comparing no-blame attribution with EU or Dutch government blame attribution conditions. Means with differing second subscripts (x through z) within columns indicate significant differences between levels of identity attachment within experimental conditions. Identity attachment scales on the national and European level were recoded into weaker and stronger in the same way. The threshold value for higher attachment was set at 4.01. Analyses with alternative recoding yielded similar results.

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

As support for the national government or partisanship provides an important alternative explanation of the perceptual screen mechanism moderating the effects of blame attribution, we also estimated the role of support for the government as robustness check. The results of this analysis indicated that participants’ perceptual screen was only based on national identity and not on support for the government,⁵ which further supports H2a.

The two-way interaction effect of responsibility attribution and European identity attachment on EU blame perceptions was nonsignificant (F(2, 669) = 0.059, p = n.s.), which is not supportive of H2b.

The interaction effect of responsibility attributions and national identity attachment on the populist antagonism attitude approached statistical significance (F(5, 715) = 2.16, p = .057, partial η² = 0.02) and the interaction effect on the representation attitude was highly significant (F(5, 715) = 7.31, p < .001, partial η² = 0.05). In support of H2a, the populist attitudes of citizens with a weaker national identity attachment were stronger in the blame conditions than in the no-blame conditions (see Table 4 for mean differences). As expected, differences between blame attribution conditions were not significant for citizens who identify strongly with the nation state.

Table 4.

Effects of Emotionalized Blame Attributions on Populist Attitudes for Different Levels of Identity Attachment.

Dependent variable	Identity attachment level	Experimental conditions									Three-way interaction effect F, Df (2, 681)	Partial η²
		No-blame attribution			EU blame attribution			Government blame attribution
		Anger	Fear	Total	Anger	Fear	Total	Anger	Fear	Total
Populist attitude: representation	Weaker national identity	5.06_a,x (1.19)	4.74_b,x (1.13)	4.92_c,x (1.09)	5.42_a,x (1.01)	5.33_d,x (1.27)	5.38_e,x (1.13)	5.36_a,x (1.19)	5.31_d,x (1.11)	5.34_e,x (1.15)	7.25**	0.07
	Stronger national identity	4.44_a,x (1.11)	4.30_b.x (1.23)	4.33_c,y (1.10)	4.66_a,y (1.22)	4.52_b,y (1.13)	4.58_c,y (1.17)	4.53_a,y (1.18)	4.70_d,x (1.08)	4.62_c,y (1.13)
	Total	4.73_a (1.19)	4.51_b (1.21)	4.63_c (1.15)	5.02_a (1.18)	4.80_b (1.23)	4.91_d (1.21)	4.94_a (1.25)	5.00_e (1.13)	4.97_f (1.19)
Populist attitude: antagonism	Weaker national identity	3.52_a,x (1.04)	3.89_b,x (1.49)	3.88_c,x (1.23)	4.64_d,x (1.32)	4.77_b,x (0.92)	4.70_e,x (1.13)	4.89_f,x (1.32)	2.50_b,x (1.00)	4.39_c,x (1.59)	3.10**	0.03
	Stronger national identity	4.23_a,y (0.99)	3.89_b,x (1.00)	3.97_c,x (1.02)	4.13_a,x (1.06)	4.05_b,y (1.12)	4.09_c,y (1.09)	4.07_a,y (1.16)	4.01_b,y (1.13)	4.04_c,x (1.14)
	Total	4.16_a (1.02)	3.87_b (1.05)	3.94_c (1.04)	4.19_a (1.10)	4.13_b (1.11)	4.16_c (1.11)	4.19_a (1.21)	3.93_b (1.13)	4.06_c (1.18)

Note. Standard deviations are reported in parentheses below means. Means with differing first subscripts (a through f) within the rows and within emotionalized style differ significantly at the p < .05 level based on independent samples t-test comparing no-blame attribution with EU or Dutch government blame attribution conditions. Means with differing second subscripts (x and y) within columns indicate significant differences between levels of identity attachment within experimental conditions. Identity attachment scales on the national and European level were recoded into weaker and stronger in the same way. The threshold value for higher attachment was set at 4.01. Analyses with alternative recoding yielded similar results.

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

We found significant interaction effects of blame attributions and European identity attachment on the populist representation attitude (F(5, 715) = 16.28, p < .001, partial η² = 0.10) and the populist antagonism attitude (F(5, 715) = 8.03, p < .001, partial η² = 0.05). In support of H2b, populist attributions of blame resulted in stronger populist attitudes on both dimensions among the people with a weaker attachment to Europe.

Overall, the results provide support for Hypothesis 2. With the exception of blame perceptions toward the EU, identity attachment functioned as a perceptual screen moderating the effects of populist blame attributions on perceptions toward the political establishment.

Effects of Emotional Blame Attributions on Blame Perceptions and Populist Attitudes

We found significant two-way interaction effects of emotionalized style and blame attributions on blame perceptions toward the EU (F(2, 681) = 3.65, p = .026, partial η² = 0.01) and the Dutch government (F(2, 681) = 3.17, p = .043, partial η² = 0.01). In line with H3a, citizens in the fear conditions were more likely to accept blame attributions to the EU than citizens in the anger conditions (see Table 3 for mean differences between experimental conditions). When blame was attributed to the government, fear also resulted in more acceptance of the blame frame than anger, but the mean differences were nonsignificant.

The significant two-way interaction effect of blame attributions and emotional style on the populist representation attitude (F(2, 681) = 2.74, p = .012, partial η² = 0.02) indicates that citizens in the fear conditions were significantly more likely to believe that politicians should, but failed to, represent the ordinary people’s will as a result of exposure to governmental blame attributions than citizens in the anger conditions (see Table 4 for mean differences). Emotionalized attributions of blame to the EU, however, did not affect any of two populist attitudes.

The results are predominantly supportive of H3a. As predicted, fear resulted in a stronger tendency to accept populist blame attributions than anger. However, this effect was only significant when blame was attributed to the EU. Populist attitudes, however, were only significantly affected by fear-emphasizing blame attributions to the government.

Identity Attachment as a Moderator of Emotional Blame Attribution Effects

In a next step, regression analyses showed how the effects of the emotional style of the message were contingent upon different levels of identity attachment. As shown in Table 5, the effects of the emotional style on governmental blame perceptions were moderated by national identity attachment. For lower levels of national identity attachment, anger resulted in stronger governmental blame perceptions than fear. In contrast, at higher levels of national identity attachment, fear resulted in stronger blame perceptions than anger (see Figure 2 for the regression lines of the interaction effects). Identity attachment to Europe did not change the relationship between emotional style and EU blame perceptions, as demonstrated by the nonintersecting lines in Figure 2.

Table 5.

Regression Model Predicting the Effects of Emotionalized Style at Different Levels of Identity Attachment.

Dependsent measures	Variable	Model I	Model II
Dependsent measures	Variable	B (SE B)	B (SE B)
Governmental blame perceptions	(Constant)	4.84 (0.13)**	4.83 (0.13)**
	Emotionalized style	−0.10 (0.18)	−0.13 (0.18)
	National identity	−0.13 (0.07)	−0.14 (0.09)
	Emotionalized style × National identity		0.41 (0.15)**
	Adjusted R²	−.01	.02
	F for change in R²		7.33**
EU blame perceptions	(Constant)	4.66 (0.12)**	4.66 (0.12)**
	Emotionalized style	0.22 (0.17)	0.22 (0.17)
	European identity	−0.13 (0.05)*	−0.15 (0.08)
	Emotionalized style × European identity		0.05 (0.11)
	Adjusted R²	.02	.02
	F for change in R²		.25
Populist attitude: representation	(Constant)	4.93 (0.12)***	4.92 (0.11)***
	Emotionalized style	0.09 (0.17)	0.04 (0.16)
	National identity	−0.12 (0.07)	−0.26 (0.08)**
	Emotionalized style × National identity		0.46 (0.14)**
	Adjusted R²	.02	.05
	F for change in R²	11.11**
Populist attitude: antagonism	(Constant)	4.16 (0.11)***	4.17 (0.11)***
	Emotionalized style	−0.01 (0.15)	−0.02 (0.15)
	European identity	−0.13 (0.05)*	−0.02 (0.08)
	Emotionalized style × European identity		−0.19 (0.10)*
	Adjusted R²	.02	.03
	F for change in R²		3.62*

Note. Effects are analyzed within blame attribution conditions. Government blame and representation attitudes are analyzed within governmental blame attribution conditions (n = 224). EU blame and populist antagonism attitudes are analyzed within EU blame attribution conditions (n = 223). National identity and European identity were centered at their means. Standard errors are reported between parentheses.

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

Figure 2.

Effects of emotionalized style on blame perceptions and populist attitudes for different levels of identity attachment.

The regression analysis points to a significant interaction effect of national identity attachment and emotional style on the populist representation attitude. For lower levels of identity attachment, anger resulted in stronger perceptions of failed representation than fear. For higher levels of identity attachment, the effect was the other way around. We also found a significant interaction effect of European identity attachment and emotionalized style on the populist antagonism attitude. As expected, fear resulted in stronger good people versus corrupt elites perceptions than anger for lower levels of European identity attachment (see Figure 2).

In sum, the results offer limited support for Hypothesis 3b. In support of H3b, fear resulted in a stronger perceived antagonism between the good people and corrupt elites than anger for citizens with a weaker attachment to Europe. In contrast to H3b, fear did not result in stronger populist attitudes and governmental blame perceptions for lower levels of national identity attachment. But how is the acceptance of blame frames contingent upon the emotional style for different levels of identity attachment?

As can be seen in Table 3, only citizens experiencing a weaker attachment to Europe in the fear conditions accepted frames attributing blame to the EU. For these citizens, EU blame perceptions were significantly weaker in the no-responsibility conditions (M = 4.15, SD = 1.34) than in the EU-responsibility conditions (M = 5.02, SD = 1.46). For governmental blame perceptions, however, fear did not result in frame congruent blame perceptions among weaker attached citizens.

As shown in Table 4, citizens experiencing a weaker attachment to national identity exposed to populist attributions of blame hold significantly stronger populist attitudes on the representation dimension than weaker attached citizens who were not exposed to blame frames. However, this effect was only found when fear was used as emotional style. For identity attachment to Europe, weaker attached citizens in both the fear and anger conditions responded to blame frames with stronger populist attitudes than those exposed to no attributions of blame. In general, the results suggest that fear resulted in stronger blame-frame congruent attitudes than anger, but only among weaker attached citizens. To answer RQ1, then, acceptance of the fear blame frame was indeed highest among lower levels of social identity attachment.

Discussion

A growing number of scholars have suggested that future research on populism and the media should investigate how populist messages are received by the people (e.g., Jagers & Walgrave, 2007; Mazzoleni, 2008). Responding to this call, this study aimed to reveal how populist communication influences what part of the electorate in the midst of the assumed populist zeitgeist. An experiment was conducted to understand how emotionalized blame attribution—the core element of populist communication—influences perceptions of blame and populist attitudes targeted at the elites.

The results indicate that blame perceptions were influenced by populist blame frames. This implies that when blame was attributed to the EU, citizens followed suit by blaming the EU. However, for blame perceptions of the national government, the emotional style had a stronger effect on blame perceptions than responsibility attributions. Populist communication thus affects blame perceptions toward the EU and the Dutch government in different ways. Populist communication that attributes blame to the national government needs to use an emotional style to be effective, whereas populist communication influences blame perceptions toward the EU by mentioning that the EU is responsible for causing the problems of the heartland. We interpret this as evidence that EU attitudes may be more volatile and prone to change by informational cues on responsibility. In contrast, opinions on the national government may be more stable, needing the populist cultivation of negative affect toward the enemies to change.

In line with Krämer’s (2014) argument of the conditionality of media populism’s effects, not all citizens are persuaded by populist messages that attribute blame to the elites. Attachment to national or European identity functions as a perceptual screen when citizens respond to populist communication. As predicted by social identity theory, people feeling close to European or Dutch identity hold a frame of reference that is biased toward their in-group. This perceptual screen motivates them to absolve the EU or the Dutch government of blame whenever populist blame frames attribute responsibility to these levels of governance.

We found that the emotionalized style of the populist message influences its effectiveness. In line with findings of earlier research, fear results in a stronger tendency to accept blame frames than anger (e.g., Nabi, 2003). Moreover, the framing effects of fear and anger depend on the level of identity attachment. On a theoretical note, this study adds to the literature on affective framing effects by demonstrating that discrete emotions may not only influence perceptions when they are measured as feelings but also influence the acceptance of frames and (populist) attitudes when they are incorporated in a communication message as style (see also Gadarian, 2010).

Although previous research has demonstrated the existence of populist attitudes among the people (Akkerman et al., 2014), this study is the first to demonstrate that media populism affects different dimensions of populist attitudes. The populist attitude that was affected most substantially concerns citizens’ perception of representation. Exposure to populist blame frames bolstered the populist perception that the ordinary people’s will is not represented by politicians, who are not capable of acting on behalf of the people. Albeit less consistently, populist blame attribution also affected people’s antagonist perceptions of society, which taps into the belief that society is divided by “the pure people” versus “the corrupt elites.” This is a highly relevant finding, as this indicates that the scope of the effects of populist attributions of blame reaches beyond blame perceptions.

In the context of this study, populist messages attributing causal responsibility for the highly salient issue of the national Labour market to the elites in the government or the EU thus activated populist schemata among citizens. Messages pointing to the failures of the elites bolstered citizens’ perception that their will should be central in political decision making, as politicians are doing a bad job in representing them. The government and the EU, in turn, were perceived as being opposed to the people.

These results provide valuable insights into the populist literature, in which it has been found that populist attitudes play an important role in predicting populist party support (e.g., Rooduijn, 2014). Advancing this literature, it can be suggested that populist communication influences preference for populist parties via the activation of populist attitudes. The electoral success of populist parties in Europe and Latin America, as well as the growing popularity of populist politicians in the U.S. can be explained in the light of issue-voting. People who interpret societal issues from a stronger populist perspective should be more inclined to vote for a political party that expresses a similar perspective (Zaller, 1992). The pervasiveness and persuasiveness of populist messages may thus have far-reaching implications for the political landscape.

How do our insights into populist communication connect to the related field of research on attributions of responsibility to the EU and the government? Research on attributions of responsibility argues that it is difficult for citizens to understand who is responsible in the intelligible background of the EU-national multilevel of governance (Karp, Banducci, & Bowler, 2003; Rudolph, 2003; Tilley & Hobolt, 2011). In line with this research, we found that citizens are not always able to distinguish between different levels of responsibility when asked to punish the culprit. For example, citizens who experience a weaker attachment to the nation state exposed to blame attribution to the government attribute more blame to the EU than the “factually responsible” national government. The lack of knowledge on governmental accountability is thus not always bridged by offering citizens more information on causal responsibility (Karp et al., 2003).

An important implication of this study is that the effectiveness of populist communication can be assessed in a systematic way. In general, populist blame attributions to the political elites only work effectively for citizens who do not identify with national or European identity, and people are more likely to accept blame attributions when fear rather than anger is emphasized as style. If the populist communicator wants to effectively shift blame from the people to the establishment, he or she should play on feelings of fear and should target his or her communication strategy at voters that do not feel attached to the out-group that is constructed as culprit. However, if the populist wants to incite populist attitudes among the people without blaming the establishment, anger may be more effective than fear for weaker attached citizens. Hence, the strategic use of emotions in populist communication should be tailored to the social identity attachment of the target group. Reasoned from these insights, the success of European populists like Wilders in the Netherlands and Le Pen in France may be due to their emphasis on negative emotions and the appeal to “ordinary citizens” who do not feel connected to the nation ruled by the culprit elites.

This study has several shortcomings. First, the effect sizes of emotionalized blame attributions were relatively modest and the design did not allow us to draw any conclusions on their duration. People changed their attitudes toward the blamed establishment with approximately 0.5 points on a 7-point scale only a few minutes after exposure, which indicates that populist attitudes were more likely to be bolstered than activated. However, these changes resulted from reading only one short populist message. If people have a preference for media content that emphasizes this communication style on a daily basis, the effects of media populism drawing on this communication style may be stronger and more lasting.

Another limitation of this study is that the sender of populist communication was kept constant across conditions. Previous studies found that party cues influence the effects of attributions of responsibility in media content (e.g., Malhotra & Kuo, 2008). Hence, the results of our study might have been different if we had manipulated the source of populist messages, as demonstrated by Sheets, Bos, and Boomgaarden (2015). Specifically, we expect that a populist source would be perceived as more credible in attributing blame than a nonpopulist source. Message acceptance, however, should be contingent upon approval of the source: People who disapprove of the populist source are less likely to be persuaded by blame frames than people who support the populist source.

Future research could further investigate how the effects of populist attributions of blame differ between populist and non-populist sources. This study, however, aimed to isolate the message effects of the populist communication strategy. It demonstrated that independent of who is communicating the populist message, citizens are affected by it. This key finding differs from previous research only finding effects of populist media cues that mentioned the populist source (e.g., Sheets et al., 2015). Hence, this study is the first to provide empirical evidence for the occurrence of message effects in the light of media populism.

It could be argued that our operationalization of citizens’ perceptual screen bias does not link up to previous research suggesting that citizens with an exclusive perception of national identity are most susceptible to persuasion by blame attributions (Carey, 2002; de Vries & van Kersbergen, 2007; Hooghe & Marks, 2003). However, our operationalization of the perceptual screen derived from different theoretical considerations and was not applied to exclusionist populism. In line with definitions of populism that are not restricted to the extreme right, the idealized nation can be conceptualized as an imagined community of the pure heartland (Anderson, 2003). Because of the corruption of politics, this heartland is betrayed. In line with this reasoning, it is plausible that not only citizens with an exclusive identity but also citizens with a weaker attachment to Europe or the nation are persuaded by populist attributions of blame. The mechanism of attachment to identity may be just as relevant for populism as partisanship is for research on attributions of responsibility.

All in all, this study demonstrates that emotionalized blame attribution can—and should—be regarded as a core feature of populist communication. Blame is most persuasive when fear toward the culprit out-group is emphasized. The populist zeitgeist resonating in political communication will be especially effective for citizens who do not feel attached to Europe or the nation state as they are least resistant to the populist blame game and most likely to interpret reality from a populist frame of mind.

Footnotes

Appendix A

Appendix B

Declaration of Conflicting Interests

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

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Michael Hameleers is a PhD candidate in political communication at the Amsterdam School of Communication Research (ASCoR) at the University of Amsterdam. The topic of his dissertation research is populism in the media. His research interests include framing, media populism, and the role of identity in media effects.

Linda Bos is an assistant professor in political communication at the Amsterdam School of Communication Research (ASCoR) at the University of Amsterdam. Her research interests include electoral behavior, quantitative research methods, (right-wing) populism, and political communication.

Claes H. de Vreese is a professor and chair of political communication and program group director of political communication and journalism at the Amsterdam School of Communication Research (ASCoR) at the University of Amsterdam. He is an adjunct professor of political science and journalism at the University of Southern Denmark. His research interests include comparative journalism research, the effects of news, public opinion, and European integration.

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