The reader’s feeling and text-based emotions: The relationship between subjective self-reports, lexical ratings, and sentiment analysis.

Werlen, Egon and Imhof, Christof and Benites, Fernando and Bergamin, Per (2019) The reader’s feeling and text-based emotions: The relationship between subjective self-reports, lexical ratings, and sentiment analysis. In: Proceedings of the 4th Swiss Text Analytics Conference (Swiss-Text 2019) 4th Swiss Text Analytics Conference (Swiss-Text 2019), 18th-19th Juni 2019, Winterthur.

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Abstract

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.

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