The reader's feeling and text-based emotions : the relationship between subjective self-reports, lexical ratings, and sentiment analysis
Egon Werlen, Christof Imhof, Fernando Benites, Per Bernard Bergamin · Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) · 2019
In this study, we examined how precisely a sentiment analysis and a word list-based lexical analysis predict the emotional valence (as positive or negative emotional states) of 63 emotional short stories. Both the sentiment analysis and the word list-based analysis predicted subjective valence, which however was predicted even more precisely when both analysis methods were combined. These results can, for example, contribute to the development of new technology-based teaching designs, in that positive or negative emotions in the texts or online-contributions of students can be assessed in automated form and transferred into instructional measures. Such instructional actions can, for example, be hints, learning support or feedback adapted to the students' emotional state.