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The European elections in 2014 were the first to be held after a long period in which EU-related news was prominent in the media. They were held after years of daily news about the euro crisis and after months of news about the popular uprising in the Ukraine against president Yanukovych, who had refused to sign the association agreement with the EU. This could have invited political parties to overcome the usual problem of low salience of EU issues by strongly profiling themselves on EU issues. Turnout at the 2014 EU elections, however, remained low, hinting that parties were unable to convert the attention for European issues into enthusiasm for their party at the European elections. This paper asks how vote choice was influenced by party campaigning on EU related issues. A news effects analysis based on a content analysis of Dutch newspapers and television, and on a panel survey among Dutch voters revealed that EU issues functioned as wedge issues: the more strongly parties were associated in the news with the euro crisis and the Ukraine, the less they succeeded in mobilizing voters.

The European elections in 2014 were the first to be held after a long period in which EU-related news was prominent in the media. They were held after years of daily news about the euro crisis and after months of news about the popular uprising in the Ukraine against president Yanukovych, who had refused to sign the association agreement with the EU. This could have invited political parties to overcome the usual problem of low salience of EU issues by strongly profiling themselves on EU issues. Turnout at the 2014 EU elections, however, remained low, hinting that parties were unable to convert the attention for European issues into enthusiasm for their party at the European elections. This paper asks how vote choice was influenced by party campaigning on EU related issues. A news effects analysis based on a content analysis of Dutch newspapers and television, and on a panel survey among Dutch voters revealed that EU issues functioned as wedge issues: the more strongly parties were associated in the news with the euro crisis and the Ukraine, the less they succeeded in mobilizing voters.

The 9/11 terrorist attacks and later attacks such as those in London and Madrid shocked the world and found their way into the newspapers of many countries. The authors study the international coverage of these events in the context of globalization versus localization and the creation of the dominant post-cold war frame of the War on Terror. Using automatic co-occurrence analysis based on the notion of associative framing, they investigate whether these events were mainly framed in a local or global way in the American, British, and Dutch press. The authors found that although proximity is still a strong determinant of attention for events, the framing of these events was more affected by the global event of 9/11 than by local considerations.

Issues that touch on the separation of powers, that is, on the relationship between parliament, government and the judiciary, and on the relationship between the Public Prosecution Service, the legal profession and the judge, have been rife in the news of the past twenty years ( for example IRT affair, acquittal of terror suspects, trial Wilders). The separation of powers is part of most Dutch definitions of the rule of law. The research resulting from this WODC publication is aimed at identifying trends and patterns in messages (from newspapers, television news bulletins, news websites, Twitter) over the past twenty years that could affect confidence in the rule of law. It was examined whether text mining, that is, automated text analysis or "content analysis", is an appropriate research tool. - Kwesties die raken aan de scheiding der machten, dat wil zeggen, aan de verhouding tussen volksvertegenwoordiging, regering en rechterlijke macht, en aan de verhouding tussen OM, de advocatuur, en de rechter waren schering en inslag in het nieuws van de afgelopen twintig jaar (bijvoorbeeld IRT-affaire, vrijspraak terreurverdachten, proces-Wilders). De scheiding der machten vormt een onderdeel van de meeste Nederlandse definities van de rechtsstaat. Het onderzoek waaruit deze WODC-publicatie voortvloeit, is gericht op het onderkennen van trends en patronen in berichten (uit dagbladen, televisienieuwsbulletins, nieuwswebsites, Twitter) van de afgelopen twintig jaar die het vertrouwen in de rechtsstaat zouden kunnen beïnvloeden. Nagegaan werd of tekstmining, dat wil zeggen, geautomatiseerde tekstanalyse of 'inhoudsanalyse', daarbij een geschikt onderzoeksmiddel is.

Analysis of political communication is an important aspect of political research. Thematic content analysis has yielded considerable success both with manual and automatic coding, but Semantic Network Analysis has proven more difficult, both for humans and for the computer. This article presents a system for an automated Semantic Network Analysis of Dutch texts. The system automatically extracts relations between political actors based on the output of syntactic analysis of Dutch newspaper articles. Specifically, the system uses pattern matching to find source constructions and determine the semantic agent and patient of relations, and name matching and anaphora resolution to identify political actors. The performance of the system is judged by comparing the extracted relations to manual codings of the same material. Results on the level of measurement indicate acceptable performance. We also estimate performance at the levels of analysis by using a case study of media authority, resulting in good correlations between the theoretical variables derived from the automatic and manual analysis. Finally, we test a number of substantive hypotheses with regression models using the automatic and manual output, resulting in highly similar models in each case. This suggests that our method has sufficient performance to be used to answer relevant political questions in a valid way.

AbstractSupervised machine learning is an increasingly popular tool for analyzing large political text corpora. The main disadvantage of supervised machine learning is the need for thousands of manually annotated training data points. This issue is particularly important in the social sciences where most new research questions require new training data for a new task tailored to the specific research question. This paper analyses how deep transfer learning can help address this challenge by accumulating "prior knowledge" in language models. Models like BERT can learn statistical language patterns through pre-training ("language knowledge"), and reliance on task-specific data can be reduced by training on universal tasks like natural language inference (NLI; "task knowledge"). We demonstrate the benefits of transfer learning on a wide range of eight tasks. Across these eight tasks, our BERT-NLI model fine-tuned on 100 to 2,500 texts performs on average 10.7 to 18.3 percentage points better than classical models without transfer learning. Our study indicates that BERT-NLI fine-tuned on 500 texts achieves similar performance as classical models trained on around 5,000 texts. Moreover, we show that transfer learning works particularly well on imbalanced data. We conclude by discussing limitations of transfer learning and by outlining new opportunities for political science research.

Growing concern about the democratic impact of automatically curated news platforms urges us to reconsider how such platforms should be designed. We propose a theoretical framework for personalised diversity nudges that can stimulate diverse news consumption on the individual level. To examine potential benefits and limitations of existing diversity nudges, we conduct an interdisciplinary literature review that synthesises theoretical work on news selection mechanisms with hands-on tools and implementations from the fields of computer science and recommender systems. Based thereupon, we propose five diversity nudges that researchers and practitioners can build on. We provide a theoretical motivation of why, when and for whom such nudges could be effective, critically reflect on their potential backfire effects and the need for algorithmic transparency, and sketch out a research agenda for diversity-aware news recommender design. Thereby, we develop concrete, theoretically grounded avenues towards facilitating diverse news consumption on algorithmically curated platforms.

Changes in political perceptions and preferences may result from the combined effects of news from various media. Estimating these combined effects requires the best possible, albeit different, measures of news obtained from self-selected mass media and social media that can be linked to panel survey data concerning perceptions and preferences. For the 2017 Dutch national elections, such data is available. Political perceptions and preferences are affected by news statements in self-selected mass media on issue positions, support and criticism, real world conditions and success and failure, in accordance with the theories on agenda setting and issue ownership, social identity, retrospective voting and bandwagon effects, respectively. Combined effects emerge because many people use both mass media and social media. The latter do more than just reinforce predispositions. Social media also have a mere exposure effect, and a multistep flow effect that amplifies news about party successes and failures from self-selected mass media.

This paper investigates the influence of news agency Algemeen Nederlands Persbureau (ANP) on the coverage and diversity of political news in Dutch national newspapers. Using computational text analysis, we analyzed the influence on print newspapers across three years (1996, 2008, and 2013) and compared influence on print and online newspapers in 2013. Results indicate that the influence of ANP on print newspapers only increased slightly. Online newspapers, however, depend heavily on ANP and are highly similar as a result of such dependence. We draw conclusions relating to the gatekeeping role of news agencies in the digital age in general, and in the context of the Netherlands in particular. Additionally, we demonstrate that techniques from the field of information retrieval can be used to perform these analyses on a large scale. Our scripts and instructions are published open-source to stimulate the use of these techniques in communication studies.