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Discursive representation of the migrant crisis in two UK broadsheets during the summer of 2015: Approaching newspaper discourse from a corpus-based and critical discourse analytical perspective
Högskolan Dalarna, Akademin Humaniora och medier, Engelska.
2017 (Engelska)Självständigt arbete på grundnivå (kandidatexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
Abstract [en]

By linguistically examining 162 articles published during the summer of 2015 in two UK broadsheets:

The Guardian (TG) and The Daily Telegraph (TDT), this essay aims to analyse the discursive representation of the ‘migrant crisis’. To do so, the representation of the social actors migrating (SAM) during the ‘crisis’ was focused on. A combined Corpus Linguistic (CL) and Critical Discourse Analysis (CDA) approach was implemented to investigate the most frequently used terms to refer to the SAM. Once the terms were found, their usage across the corpora was examined by looking at frequency distributions. Next, collocates of the terms referring to SAM were analysed by way of Van Leeuwen’s (2008) Social Actor Network. Collocate and concordance analyses helped to show how the SAM were represented in the articles and how the representation varied across the two newspapers. The results of the analyses indicated that the most frequent terms used to refer to the SAM were migrant, people and refugee. It also indicated differences in connotations of those three words, with refugee ‘sympathetically’ connoted, migrant negatively connoted and people connoted both negatively and positively. The overall conclusion was that the SAM’s representation was more ‘sympathetic’ in TG than in TDT.

Ort, förlag, år, upplaga, sidor
2017.
Nyckelord [en]
Van Leeuwen’s Social Actor Network, corpus-based approach, CDA, frequencies, collocates, concordance
Nationell ämneskategori
Studier av enskilda språk
Identifikatorer
URN: urn:nbn:se:du-25484OAI: oai:DiVA.org:du-25484DiVA, id: diva2:1119846
Tillgänglig från: 2017-07-05 Skapad: 2017-07-05 Senast uppdaterad: 2018-01-13

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