A corpus linguistic approach to meaning-making patterns in surveillance discourse

Research output: ThesisDoctoral Thesis


This thesis analyses meaning-making patterns in surveillance discourse using a corpus linguistic approach. As a widespread and contested social issue, surveillance lends itself well to an analysis of meaning in discourse. The thesis puts forward three principles of meaning-making that are explored empirically: (i) meaning evolves with the discourse, (ii) meaning emerges via comparison and (iii) meaning takes shape in co-occurrence patterns. The first principle states that meaning is dynamic and changes across text types and over time. Comparison is therefore necessary to recognise meaning (see principle ii). According to the final principle, meaning can be identified in co-occurrence patterns in discourse. The thesis follows the three principles by taking a comparative approach to co-occurrence patterns of surveillance in corpora that reflect three different social domains: academic discourse, represented by a journal that specialises on surveillance, digital discourse, represented by blog posts that are related to surveillance and, finally, news discourse, represented by a newspaper corpus. The analysis highlights the complexity of surveillance discourses. The thesis develops a methodology that combines traditional corpus linguistic techniques with more qualitative and multimodal elements. By incorporating theoretical frameworks from other disciplines, the thesis demonstrates the interdisciplinary potential of corpus linguistics.
Original languageEnglish
Awarding Institution
Award date10 Dec 2019
Publication statusPublished - 2019


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