SFL-BASED APPRAISAL THEORY AS AN EFFECTIVE METHOD FOR EMOTION DETECTION IN PUBLIC DISCOURSE

Abstract

This article delves into the emotional analysis of motivational speeches, a vital subtype of public discourse recognized for its emotive character and strategic linguistic devices aimed at influencing and engaging the audience. Within this research, efforts are dedicated to unveiling the intricate facets of emotional expression revealed through lexical choices and grammatical structures across various domains, including politics, education, and business. To systematically process and analyze data, this research leverages the UAM Corpus Tool (O’Donnell, 2008) and AntConc software (Anthony, 2005), with a particular focus on the Key-Word-In-Context (KWIC) analysis. Employing a corpus-driven analytical approach firmly rooted in the principles of SFLbased Appraisal Theory, this study effectively identifies and delineates the full spectrum of emotional expressions within motivational speeches. SFLbased Appraisal Theory emerges as the central and most effective method for unraveling the complex emotional landscape within motivational speeches. This tool is combined with rigorous corpus analysis to unveil significant linguistic patterns and markers representing a spectrum of emotional dimensions, particularly through the categories of Affect, Attitude, Engagement, and Graduation. Notably, within the Affect category of Appraisal Theory, specific attention is given to the meticulous analysis of the word “feel” and its combinations with adjectives, nouns, and other parts of speech. This analysis sheds light on how these linguistic constructs contribute to the expression and interpretation of emotions in motivational speeches. Consequently, the abovementioned analysis contributes significantly to a deeper understanding of the persuasive strategies strategically deployed within this genre of discourse.