A Multimodal Corpus-Based Study of american career weblogs

Abstract

The article describes the application of multimodal corpus-based methodologies to the study of the popular American career blogs. The research is carried out within the framework of the theory of multimodal discourse analysis. Quantitative and qualitative methods have been applied in order to identify and explain different aspects of verbal and graphic modes convergence. Two corpora have been compiled by the authors for the purposes of the research. Both corpora contain multimodal annotations to browse and search for relevant textual and visual materials. The corpus software used in this research is UAM CorpusTool and UAM ImageTool, they include frequency and keywords search, statistical processing of visual images annotations and their combinations with keywords. A collection of texts along with the images (photos, graphics and illustrations) has been analyzed to investigate how verbal and non-verbal modes work together to convey the holistic meaning of the message. The results suggest that verbal and graphic modes are non-competing but mutually supportive and complementary. The analysis has proved that the specified modes have different meaning potential: words can add focus, identification, precision, and perspective to a pictorial representation while images add emotional, expressive and connotative value to the text.