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2011
Springer

Using a Heterogeneous Dataset for Emotion Analysis in Text

8 years 2 months ago
Using a Heterogeneous Dataset for Emotion Analysis in Text
In this paper, we adopt a supervised machine learning approach to recognize six basic emotions (anger, disgust, fear, happiness, sadness and surprise) using a heterogeneous emotion-annotated dataset which combines news headlines, fairy tales and blogs. For this purpose, different features sets, such as bags of words, and N-grams, were used. The Support Vector Machines classifier (SVM) performed significantly better than other classifiers, and it generalized well on unseen examples.
Soumaya Chaffar, Diana Inkpen
Added 24 Aug 2011
Updated 24 Aug 2011
Type Journal
Year 2011
Where AI
Authors Soumaya Chaffar, Diana Inkpen
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