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...)

The classic definition of content analysis is the one by Bernard Berelson (1952, 18): “a research technique for the objective, systematic and quantitative description of the manifest content of communication.” Although this definition is very broad, in media and communication studies it usually implies the manual coding of communication content whereby every article is coded according to characteristics of the article. An example would be the application of the categories of Erving Goffman’s book Gender Advertisements (1979) to an actual sample of advertisements. The results of that research would include, for instance, how many stereotypes are used, which stereotypes are used more often in the representation of women with different ethnicities, and for which product categories stereotypes are more often used. Within a broad definition of content analysis, corpus linguistics could also be defined as a form of content analysis, although media and communication scholars do not typically think of corpus linguistics when the notion of content analysis is mentioned. Richard Nordquist defines the idea of corpus linguistics as follows: “Corpus linguistics is the study of language based on large collections of ‘real life’ language use stored in corpora (or corpuses) – computerized databases created for linguistic research. It is also known as corpus-based studies.” (Nordquist 2019, n. p.) Corpus Statistics Analysis allows the automatic analysis of very large corpora. This strategy depends on two theoretical notions and their attendant analytical tools, i.e., keyness and collocation (Baker et al. 2008). Keyness is the frequency of particular words of clusters or words in certain corpora, while collocation of words occurs within a predetermined span of words. Within the OPPORTUNITIES project, the analysis of content will be applied to the analysis of tweets by politicians in four countries under study, namely Austria, Germany, Hungary, and Italy.

⇢ see also Frames of migration, Quantitative media studies

References and further reading:

Baker, Paul; Gabrielatos, Costas; Khosravinik, Majid; Krzyzanowski, Michal; McEnery, Tony and Wodak, Ruth. 2008. “A Useful Methodological Synergy? Combining Critical Discourse Analysis and Corpus Linguistics to Examine Discourses of Refugees and Asylum Seekers in the UK Press.” In Discourse & Society. 19.3: 273–305.

Berelson, Bernard. 1952. Content Analysis in Communication Research. Glencoe: Free Press.

Goffman, Erving. 1979. Gender Advertisements. London: Palgrave.

Nordquist, Richard. 2019. “Definition and Example of Corpus Linguistics.” Thought.Co. URL:

Work Package: 2, 4, 5

[DC / LH / SM]