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In recent decades, so-called universal welfare states have experienced considerable immigration from non-Western countries and, accordingly, rising levels of ethnic diversity. On that basis, scholars have debated how ethnic diversity affects public opinion in recipient societies. The debate is to a significant extent shaped by studies of American public opinion, where public opinion on some issues is widely considered 'racialized', i.e. in part based on attitudes toward racial outgroups. The dissertation examines whether by the same token, political attitudes in universal welfare states can become 'ethnicized', i.e. in part based on attitudes toward ethnic outgroups. The existing literature has tended to focus on the issue of welfare, where the expectation is that ethnic diversity will diminish public support. I outline a theoretical framework which explains why political attitudes can be ethnicized, but also why it is more likely for some issues (such as European integration or crime) than others (such as welfare). The dissertation includes four stand-alone articles illustrating the influence of group identities in political cognition. Compared to the existing literature, they suggest that ethnicization is at once more limited (in that it is unlikely for the most widely discussed issue, welfare) and more pervasive (in that it can arise from local contexts as well as from media). Ethnicization of attitudes is one way in which immigration can influence political life, even when the political agenda ostensibly revolves around something else.

Despite concerns about the effects of pro-Russian disinformation on Western public opinion, evidence of its reach remains scarce. We hypothesize that conservative individuals will be more likely than liberals to be potentially exposed to pro-Russian disinformation in digital networks. We evaluate the hypothesis using a large data set of U.S.-based Twitter users, testing how ideology is associated with disinformation about the 2014 crash of the MH17 aircraft over eastern Ukraine. We find that potential exposure to disinformation is concentrated among the most conservative individuals. Moving from the most liberal to the most conservative individuals in the sample is associated with a change in the conditional probability of potential exposure to disinformation from 6.5% to 45.2%. We corroborate the finding using a second, validated data set on individual party registration. The results indicate that the reach of online, pro-Russian disinformation into U.S. audiences is distinctly ideologically asymmetric.

Recent studies of economic voting have focused on the role of the local economy, but with inconclusive results. We argue that while local economic conditions affect incumbent support on average, the importance of the local economy varies by citizens' interactions with it. More recent and frequent encounters with aspects of the local economy make those aspects more salient and, in turn, feature more prominently in evaluations of the incumbent government. We label this process "context priming." We provide evidence for these propositions by studying local housing markets. Linking granularly detailed data on housing prices from Danish public registries to both precinct-level election returns and an individual-level panel survey, we find that when individuals interact with the housing market, their support for the incumbent government is more responsive to changes in local housing prices. The study thus provides a framework for understanding when citizens respond politically to the local economy.

Recent studies of economic voting have focused on the role of the local economy, but with inconclusive results. We argue that while local economic conditions affect incumbent support on average, the importance of the local economy varies by citizens' interactions with it. More recent and frequent encounters with aspects of the local economy makes those aspects more salient and in turn feature more prominently in evaluations of the incumbent government. We label this process 'context priming'. We provide evidence for these propositions by studying local housing markets. Linking granularly detailed data on housing prices from Danish public registries to both precinct-level election returns and an individual-level panel survey, we find that when individuals interact with the housing market, their support for the incumbent government is more responsive to changes in local housing prices. The study thus provides a framework for understanding when citizens respond politically to the local economy. ; Recent studies of economic voting have focused on the role of the local economy, but with inconclusive results. We argue that while local economic conditions affect incumbent support on average, the importance of the local economy varies by citizens' interactions with it. More recent and frequent encounters with aspects of the local economy make those aspects more salient and, in turn, feature more prominently in evaluations of the incumbent government. We label this process "context priming." We provide evidence for these propositions by studying local housing markets. Linking granularly detailed data on housing prices from Danish public registries to both precinct-level election returns and an individual-level panel survey, we find that when individuals interact with the housing market, their support for the incumbent government is more responsive to changes in local housing prices. The study thus provides a framework for understanding when citizens respond politically to the local economy.

Assigning political actors positions in ideological space is a task of key importance to political scientists. In this paper we compare estimates obtained using the automated Wordscores and Wordfish techniques, along with estimates from voters and the Comparative Manifesto Project (CMP), against expert placements. We estimate the positions of 254 manifestos across 33 elections in Germany and Denmark, two cases with very different textual data available. We find that Wordscores approximately replicates the CMP, voter, and expert assessments of party positions in both cases, whereas Wordfish replicates the positions in the German manifestos only. The results demonstrate that automated methods can produce valid estimates of party positions, but also that the appropriateness of each method hinges on the quality of the textual data. Additional analyses suggest that Wordfish requires both longer texts and a more ideologically charged vocabulary in order to produce estimates comparable to Wordscores. The paper contributes to the literature on automated content analysis by providing a comprehensive test of convergent validation, in terms of both number of cases analyzed and number of validation measures.

Assigning political actors positions in ideological space is a task of key importance to political scientists. In this paper we compare estimates obtained using the automated Wordscores and Wordfish techniques, along with estimates from voters and the Comparative Manifesto Project (CMP), against expert placements. We estimate the positions of 254 manifestos across 33 elections in Germany and Denmark, two cases with very different textual data available. We find that Wordscores approximately replicates the CMP, voter, and expert assessments of party positions in both cases, whereas Wordfish replicates the positions in the German manifestos only. The results demonstrate that automated methods can produce valid estimates of party positions, but also that the appropriateness of each method hinges on the quality of the textual data. Additional analyses suggest that Wordfish requires both longer texts and a more ideologically charged vocabulary in order to produce estimates comparable to Wordscores. The paper contributes to the literature on automated content analysis by providing a comprehensive test of convergent validation, in terms of both number of cases analyzed and number of validation measures.