MULTIMODAL APPROACHES TO BUSINESS NEWS DISCOURSE MEDIATED ON THE INTERNET AND TELEVISION

Abstract

The dissertation examines how business news networks, such as Bloomberg, CNBC, FOX Business, and Reuters represent social actors and events in business news discourse mediated on the internet. Through the systematic analysis of a data sample consisting of 200 video clips and associated web pages, the dissertation explores how specific events are contextualized through the complex multimodal interplay of text, imagery and dynamic media.

The data is approached from a multidisciplinary perspective by drawing upon complementary theoretical perspectives, methodologies and applied frameworks from social semiotics, discourse analysis and conversation analysis, which are adapted to the analysis of multimodal data within a digital software environment.

To obtain a more holistic view of the distinctive representational styles that are adopted by different business news networks, the analysis is further aided by the application of low- and mid-level computational visualization techniques in identifying trends and patterns in the annotated data.