Identifying Expressions of Emotion in Text
Lecture notes in computer sciencePublished 18 August 2007
Saima Aman, Stan Śzpakowicz
Citations449
SJR quartileQ2
SJR score0.35
SNIP0.55
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TL;DR
An emotion annotation task of identifying emotion category, emotion intensity and the words/phrases that indicate emotion in text is described and results of an annotation agreement study on a corpus of blog posts are presented.
Abstract
Finding emotions in text is an area of research with wide-ranging applications. We describe an emotion annotation task of identifying emotion category, emotion intensity and the words/phrases that indicate emotion in text. We introduce the annotation scheme and present results of an annotation agreement study on a corpus of blog posts. The average inter-annotator agreement on labeling a sentence as emotion or non-emotion was 0.76. The agreement on emotion categories was in the range 0.6 to 0.79; for emotion indicators, it was 0.66. Preliminary results of emotion classification experiments show the accuracy of 73.89%, significantly above the baseline.
Keywords
Computer Science
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