Recognition of Emotions in Czech Newspaper Headlines
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Date
2011-04
Authors
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
With the growth of internet community, many different text-based documents are produced. Emotion detection and classification in text becomes very important in human-machine interaction or in human-to-human internet communication with this growth. This article refers to this issue in Czech texts. Headlines were extracted from Czech newspapers and Fear, Joy, Anger, Disgust, Sadness, and Surprise emotions are detected. In this work, several algorithms for learning were assessed and compared according to their accuracy of emotion detection and classification of news headlines. The best results were achieved using the SVM (Support Vector Machine) method with a linear kernel, where the presence of the dominant emotion or emotions was analyzed. For individual emotions the following results were obtained: Anger was detected in 87.3 %, Disgust 95.01%, Fear 81.32 %, Joy 71.6 %, Sadness 75.4 %, and Surprise 71.09 %.
Description
Citation
Radioengineering. 2011, vol. 20, č. 1, s. 39-47. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2011/11_01_039_047.pdf
http://www.radioeng.cz/fulltexts/2011/11_01_039_047.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en