Sentiment Analysis as a Quality Assurance Tool in Translator Training: A Pedagogical Case Study

This paper presents a pedagogical case study on the use of sentiment analysis as a quality assurance tool in translator training. Conducted at the University of Alcalá (Spain), the exercise involved students analysing the sentiment of English source texts and their Spanish translations, focusing on neutrality coefficients ranging from -1 to +1. Results showed that sentiment analysis offers a promising complement to traditional quality assessment, particularly for politically sensitive texts where tonal fidelity is critical. Students found the activity both engaging and useful for developing affective sensitivity. Although the study was limited to a single cohort and relied on one AI model, the outcomes support the incorporation of sentiment analysis into translator education. With further practice, this method could be transferred to professional workflows, offering Language Service Providers an additional tool to ensure emotional and pragmatic consistency between source and target texts.