Successful collaboration begins with a shared language, hence the need for a glossary. This joint effort of contributors from several teams ensures, on the one hand, terminological and conceptual coherence across not only our theoretical approaches, but also the qualitative case studies and quantitative research conducted in OPPORTUNITIES. On the other hand, our glossary facilitates communication between the academic side of the project and the fieldwork conducted by NGOs, uniting our teams working from Austria, Belgium, France, Germany, Ghana, Italy, Mauritania, the Netherlands, Portugal, Romania and Senegal.

For more information about the Structure and Objectives of the Glossary, click here...)

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Quantitative media studies

Complementary to the qualitative analysis of narratives in the OPPORTUNITIES project, there will be four strands of quantitative analysis. The first instance of quantitative analysis is a secondary study of data gathered in the European Social Survey. This secondary analysis uses the landmark ESS survey data to trace the evolution of immigration attitudes across different subgroups of the European population. The second one is a survey analysis (see also “Survey analysis”), where the immigration attitudes of the population in four European countries will be studied (Austria, Germany, Hungary, and Italy). Complementary insights will be gained by data in the Horizon 2020 project HumMingBird (see For both projects, the same questionnaire is used. Data have been gathered mid2021 in the four OPPORTUNITIES countries and additionally in Belgium, Spain, and Sweden. A third application of a quantitative method is the corpus analytical study of tweets by politicians. The words used in tweets by politicians in the four countries will be compared, searching for news frames (see “News frames”). The fourth application of quantitative analysis will be a social network analysis (see “Social network analysis”). Whereas a corpus analysis provides insights into the word usage of politicians (see “Content analysis and corpus linguistics”), the social network analysis provides insights into who follows whom, and who retweets messages from whom. Next to the focus on content (in the corpus analytical research), there will be a focus on the interaction structures among tweets by politicians.

⇢ see also content analysis and corpus linguistics, news frames, social network analysis, survey analysis

Category: A

Work Package: 4, 5

[DC / LH / SM