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Publication type: Conference paper
Type of review: Peer review (publication)
Title: The reader's feeling and text-based emotions : the relationship between subjective self-reports, lexical ratings, and sentiment analysis
Authors: Werlen, Egon
Imhof, Christof
Benites, Fernando
Bergamin, Per B.
et. al: No
DOI: 10.21256/zhaw-18859
Proceedings: Proceedings of the 4th edition of the Swiss Text Analytics Conference
Editors of the parent work: Cieliebak, Mark
Tuggener, Don
Benites, Fernando
Conference details: SwissText 2019, Winterthur, 18 - 19 June 2019
Issue Date: Sep-2019
Publisher / Ed. Institution: CEUR Workshop Proceedings
Language: English
Subject (DDC): 400: Language, linguistics
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.
Fulltext version: Published version
License (according to publishing contract): CC BY 4.0: Attribution 4.0 International
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Appears in collections:Publikationen School of Engineering

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