A CORPUS-ASSISTED STUDY OF ATTITUDE OF GRATITUDE IN THE ACKNOWLEDGEMENT SECTION OF PHD THESES

Abstract

Systemic Functional Linguistics (SFL) is founded on interpersonal, experiential, and textual meta-functions. Halliday and Matthiesen (2014) emphasise that language users make lexicogrammatical choices based on these meta-functions to convey intended meanings, such as expressing emotions or sharing information. The Appraisal theory by Martin and White (2005) builds on Halliday’s interpersonal meanings and focuses on evaluating attitudinal expressions in discourse. This study has applied this theory to analyse the evaluative language in the acknowledgement sections of PhD theses, where researchers express gratitude to key contributors. This study utilised corpus-based quantitative methodology to analyse the acknowledgements of 50 PhD theses in linguistics and literature, downloaded from the HEC Pakistan repository. Using AntConc (version 3.5.8), concordance lines were extracted to examine three types of attitude markers: affect (personal feelings), judgment (evaluation of people), and appreciation (assessment of things or events). The results reveal that the acknowledgement language reflects the authors' emotional responses and gratitude toward those who aided their research. These acknowledgements provide lexicogrammatical evidence of positive interpersonal relationships. While Appraisal theory includes three sub-categories [attitude, graduation, and engagement], this study focuses on attitude, highlighting the affective and evaluative dimensions of the researchers’ language choices.