Title
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Towards an empirically grounded framework for emotion analysis
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Author
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Abstract
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The first step in training a system for automatic emotion detection consists of manual data annotation. Because there is no consensus on a standard emotion framework, we established a label set which is justified both theoretically and practically. Frequency and cluster analysis of 229 tweet annotations resulted in a label set containing the 5 emotions Love, Joy, Anger, Nervousness and Sadness. Our label set shows fair resemblance to Ekman's basic emotions, but due to our data-driven approach, our label set is much more grounded in the task (emotion detection) and the domain (Dutch tweets). |
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Language
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English
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Source (book)
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HUSO 2019, the Fifth International Conference on Human and Social Analytics
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Publication
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IARIA
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2019
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ISBN
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978-1-61208-725-2
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Volume/pages
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p. 11-16
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