Identifying disputants’ attitudinal variations in family mediations: A data mining approach

Abstract

This article combines linguistic analysis and data mining methods to explore variations in speakers’ evaluative meaning-making in conflict talks. It focuses on conflict style construction through evaluative language, specifically how disputants advance attitudes. The corpus consists of 230 minutes of family mediation talks involving 12 divorcing spouses. The research draws from the Appraisal framework to analyse evaluative meaning-making at a discourse semantics level, capturing both explicit and implicit attitudes, as well as the scaling and dialogic framing of attitudes. Data exploration uses clustering algorithms via RStudio to identify variations in disputants’ discursive behaviour. The findings uncover three conflict styles based on disputants’ preference for attitude advancement formulations, with varying degrees of assertiveness and forcefulness. This study’s contributions include a holistic treatment of evaluative meaning-making, the marriage of digital tools to nuanced linguistic annotation, and a novel interpretation for conflict style. The findings offer fresh insights into disputants’ discursive self-presentation in confrontational exchanges.