Semantic Network Analysis: Techniques for Extracting, Representing, and Querying Media Content

Harmelen, F.A.H. [Promotor]van Kleinnijenhuis, J. [Promotor]Schlobach, K.S. [Copromotor

The impact of the explosion of EU news on voter choice in the 2014 EU Elections

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

Quantitative analysis of large amounts of journalistic texts using topic modelling

The huge collections of news content which have become available through digital technologies both enable and warrant scientific inquiry, challenging journalism scholars to analyse unprecedented amounts of texts. We propose Latent Dirichlet Allocation (LDA) topic modelling as a tool to face this challenge. LDA is a cutting edge technique for content analysis, designed to automatically organize large archives of documents based on latent topics, measured as patterns of word (co-)occurrence. We explain how this technique works, how different choices by the researcher affect the results and how the results can be meaningfully interpreted. To demonstrate its usefulness for journalism research, we conducted a case study of the New York Times coverage of nuclear technology from 1945 to the present, partially replicating a study by Gamson and Modigliani. This shows that LDA is a useful tool for analysing trends and patterns in news content in large digital news archives relatively quickly