Detail publikace

Recognition of Emotions in Czech Newspaper Headlines

BURGET, R. KARÁSEK, J. SMÉKAL, Z.

Originální název

Recognition of Emotions in Czech Newspaper Headlines

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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 %.

Klíčová slova

Emotion corpus, Emotion detection, Emotion classification, Text mining, Czech, artificial intelligence

Autoři

BURGET, R.; KARÁSEK, J.; SMÉKAL, Z.

Rok RIV

2011

Vydáno

11. 3. 2011

ISSN

1210-2512

Periodikum

Radioengineering

Ročník

2011

Číslo

1

Stát

Česká republika

Strany od

1

Strany do

9

Strany počet

9

BibTex

@article{BUT50998,
  author="Radim {Burget} and Jan {Karásek} and Zdeněk {Smékal}",
  title="Recognition of Emotions in Czech Newspaper Headlines",
  journal="Radioengineering",
  year="2011",
  volume="2011",
  number="1",
  pages="1--9",
  issn="1210-2512"
}