This paper presents an agent-based model explaining voter knowledge in the context of electoral competition. It shows that a set of simple behavioral rules implemented by voters, parties and media outlets generates novel (and testable) predictions regarding the mass-mediated underpinnings of aggregated voter knowledge and party representativeness. More specifically, it finds that increasing competition among media outlets has a positive effect on the political knowledge of the electorate at large. It also finds that increasing media competition leads to parties that are more accountable to the median voter, but only when voters care about the quality of the news alone.
Recent empirical workin the study of political sophistication finds that citizens' knowledge of politics is not only a function of their individual characteristics but also depends on the supply of information from their environment (the 'information environment'). Yet this literature does not address the question of how the information environment may be shaped by institutional factors. This article aims to fill this void. It first argues that the relationship between a government and the media affects the information that is available to individual citizens. Using cross-national data, it then finds that less government interference with the media (1) positively affects political learning and (2) moderates the individual-level effect of education on learning.
AbstractThe European Union's Economic Partnership Agreements (EPAs) with countries in the African, Caribbean and Pacific (ACP) group are touted as a new form of equitable engagement. However, many argue that the EPAs simply substitute a different form of political and economic domination. In this paper, we consider if the siting of meetings has a substantive impact on EPA outcomes or media reporting thereof. Using a difference‐in‐difference like approach we evaluate if the tone and polarity of media reports about the EPAs during periods of 'home' meetings in the ACP countries differs from media reports during 'away' meetings in the EU. Using two different datasets we arrive at differing results, leading to inconclusive overall findings. While we suspect that the alternating meeting site norm has implications for EPA process and outcomes, further research will be needed to uncover the precise nature of these effects.
ObjectiveDemocratic governance requires that policy outcomes and public demand for policy be linked. While studies have shown empirical support for such a relationship in various policy domains, empirical evidence also indicates that the public is relatively unaware of policy outputs. This raises a puzzle: Why do policy outputs influence public attitudes if the public knows little about them?MethodsThis study seeks to address this paradox by examining the conditioning role of media coverage. We rely on data derived from the Policy Agendas Project in the United States, allowing us to analyze the relationship between policy outcomes, public preferences, and newspaper content across a long span of time (1972–2007).ResultsOur results indicate that public policy preferences respond to policy outputs, and that this relationship is strengthened by greater media attention to a policy area. Importantly, our findings also indicate that without media attention to a policy area, there is no direct effect of policy outputs on public demand for policy.ConclusionsMedia coverage appears to be a key factor for public responsiveness to occur. In the absence of policy coverage by the media, public responsiveness to policy outputs is greatly reduced.
AbstractThis article investigates prime ministers' communication strategies during the most recent economic crisis in Europe. It argues that when electoral risk is high but governments' policy options are severely limited, prime ministers will use specific communication strategies to mitigate electoral risks. Two such communication strategies are analysed – issue engagement and blame shifting – by applying state‐of‐the‐art quantitative text analysis methods on 5,553 speeches of prime ministers in nine European Union member states. Evidence is found for both strategies. Prime ministers talk about the economy more in response to both high (domestic) unemployment and low (domestic) gross domestic product growth. Furthermore, it is found that the (domestic) unemployment rate is the most consistent predictor of blame shifting: as the domestic unemployment rate goes up, this is followed by an increase in blame shifting towards banks, Greece and the Troika of the European Commission, the European Central Bank and the International Monetary Fund.
How do mainstream political executives cue their politicised constituencies on European integration? Moving beyond static expectations that EU politicisation induces executives to either undermine, defuse or defend integration, this article theorises executives' incentives under different configurations of public and partisan Euroscepticism in their home countries. Expectations are tested on the sentiment and complexity that executives attach to European integration in almost 9,000 public speeches delivered throughout the Euro Crisis. It is found that national leaders faced with sceptical public opinion and low levels of partisan Euroscepticism rhetorically undermine integration, whereas European Commissioners faced with similar conditions are prone to defend it. These responses intensify disproportionally with growing public Euroscepticism, but are moderated by Eurosceptic party strength in surprising ways. When such challenger parties come closer to absorbing the Eurosceptic potential in public opinion, executive communication turns more positive again but also involves less clear rhetorical signals. These findings move beyond existing uniform expectations on mainstream responses to Eurosceptic challenges and highlight the relevance of different domestic configurations of EU politicisation.
How do mainstream political executives cue their politicised constituencies on European integration? Moving beyond static expectations that EU politicisation induces executives to either undermine, defuse or defend integration, this article theorises executives' incentives under different configurations of public and partisan Euroscepticism in their home countries. Expectations are tested on the sentiment and complexity that executives attach to European integration in almost 9,000 public speeches delivered throughout the Euro Crisis. It is found that national leaders faced with sceptical public opinion and low levels of partisan Euroscepticism rhetorically undermine integration, whereas European Commissioners faced with similar conditions are prone to defend it. These responses intensify disproportionally with growing public Euroscepticism, but are moderated by Eurosceptic party strength in surprising ways. When such challenger parties come closer to absorbing the Eurosceptic potential in public opinion, executive communication turns more positive again but also involves less clear rhetorical signals. These findings move beyond existing uniform expectations on mainstream responses to Eurosceptic challenges and highlight the relevance of different domestic configurations of EU politicisation.
AbstractHow do mainstream political executives cue their politicised constituencies on European integration? Moving beyond static expectations that EU politicisation induces executives to either undermine, defuse or defend integration, this article theorises executives' incentives under different configurations of public and partisan Euroscepticism in their home countries. Expectations are tested on the sentiment and complexity that executives attach to European integration in almost 9,000 public speeches delivered throughout the Euro Crisis. It is found that national leaders faced with sceptical public opinion and low levels of partisan Euroscepticism rhetorically undermine integration, whereas European Commissioners faced with similar conditions are prone to defend it. These responses intensify disproportionally with growing public Euroscepticism, but are moderated by Eurosceptic party strength in surprising ways. When such challenger parties come closer to absorbing the Eurosceptic potential in public opinion, executive communication turns more positive again but also involves less clear rhetorical signals. These findings move beyond existing uniform expectations on mainstream responses to Eurosceptic challenges and highlight the relevance of different domestic configurations of EU politicisation.
Applications of automated text analysis measuring topics, ideology, sentiment or even personality are booming in fields like political science and political psychology. These developments are to be applauded as they bring about novel insights about politics using new sources of (unstructured) data. However, a divide exists between work in both disciplines using text as data. In this paper we argue in favor of more integration across disciplinary boundaries, structuring our case around four key issues in the research process: (i) sampling text; (ii) authorship as meta data; (iii) pre-processing text; (iv) analyzing text. Along the way we demonstrate that an assessment of speaker characteristics may crucially depend on the text sources under study, and that the use of sentiment words correlates with estimates of policy positions, with implications for interpretation of the latter. As such, this paper contributes to a critical discussion about the merits of automated text analysis methods in political psychology and political science, with an eye towards advancing the considerable potential of text as data in the study of politics.
Applications of automated text analysis measuring topics, ideology, sentiment or even personality are booming in fields like political science and political psychology. These developments are to be applauded as they bring about novel insights about politics using new sources of (unstructured) data. However, a divide exists between work in both disciplines using text as data. In this paper we argue in favor of more integration across disciplinary boundaries, structuring our case around four key issues in the research process: (i) sampling text; (ii) authorship as meta data; (iii) pre-processing text; (iv) analyzing text. Along the way we demonstrate that an assessment of speaker characteristics may crucially depend on the text sources under study, and that the use of sentiment words correlates with estimates of policy positions, with implications for interpretation of the latter. As such, this paper contributes to a critical discussion about the merits of automated text analysis methods in political psychology and political science, with an eye towards advancing the considerable potential of text as data in the study of politics. ; peerReviewed ; publishedVersion
In: Political analysis: PA ; the official journal of the Society for Political Methodology and the Political Methodology Section of the American Political Science Association, Band 26, Heft 4, S. 417-430
Automated text analysis allows researchers to analyze large quantities of text. Yet, comparative researchers are presented with a big challenge: across countries people speak different languages. To address this issue, some analysts have suggested using Google Translate to convert all texts into English before starting the analysis (Lucas et al. 2015). But in doing so, do we get lost in translation? This paper evaluates the usefulness of machine translation for bag-of-words models—such as topic models. We use the europarl dataset and compare term-document matrices (TDMs) as well as topic model results from gold standard translated text and machine-translated text. We evaluate results at both the document and the corpus level. We first find TDMs for both text corpora to be highly similar, with minor differences across languages. What is more, we find considerable overlap in the set of features generated from human-translated and machine-translated texts. With regard to LDA topic models, we find topical prevalence and topical content to be highly similar with again only small differences across languages. We conclude that Google Translate is a useful tool for comparative researchers when using bag-of-words text models.