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Statistical Analysis: Metaphor recognition in Business Texts

Statistical Analysis: Metaphor recognition in Business Texts

Veronica Zima-Smith (ORCID: )
  • Grant DOI 10.55776/P14822
  • Funding program Principal Investigator Projects
  • Status ended
  • Start May 1, 2001
  • End December 31, 2002
  • Funding amount € 8,458
  • Project website

Disciplines

Linguistics and Literature (100%)

Keywords

    METAPHOR RECOGNITION, STATISTICAL ANALYSIS, BUSINESS ENGLISH, SIGNIFICANT EFFECTS, READING COMPREHENSION, LANGUAGE LEARNING

Abstract

The proposed project is an investigation into advanced language learners` ability to recognise metaphor in business texts in English. The main hypothesis is that writers of journalistic texts exploit metaphor to encode particular value judgements and comments on business practice. These metaphors are deliberately chosen to enhance text cohesion and form a coherent, conceptual framework in the texts. Although the underlying conceptual categories may be known to the language learners (here predominantly Austrians), the fact that these concepts are expressed by a variety of lexemes, which may be unknown, or unrecognisable because of their incongruity in the context, can hinder comprehension of the whole text. This approach to the study of reading comprehension through metaphor recognition attempts to lay bare the interaction between text and reader, focusing on the role of metaphorical chains as text-structuring phenomena. In this respect it differs from other types of quantitative discourse analysis which tend to neglect the role of the reader. It also includes a didactic component: the reader is at the same time a language learner. By applying the methods of descriptive and inferential statistics, the project seeks to investigate the extent to which factors such as choice of university subject, language proficiency, length of study, school background, experience of English-speaking countries, reading preferences influence the ability to recognise metaphorical expressions. The population consists of 250 students at the University of Klagenfurt, studying English and Business Administration, res-pective-ly. Relevant data have already been collected and coded for a computer-based qualitative analysis. By converting these codes, the data for a statistical analysis can be relatively easily extracted, enabling the data to be exploited statistically without further coding. Funding is sought for the data conversion, statistical analyses and interpretation of results. Key Words Metaphor Recognition Statistical Analysis Business English Significant Effects Reading Comprehension Language Learning

Research institution(s)
  • Universität Klagenfurt - 100%

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