|
Title
|
|
|
|
Towards an empirically grounded framework for emotion analysis
| |
|
Author
|
|
|
|
| |
|
Abstract
|
|
|
|
| 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). |
| |
|
Language
|
|
|
|
English
| |
|
Source (book)
|
|
|
|
HUSO 2019, the Fifth International Conference on Human and Social Analytics
| |
|
Publication
|
|
|
|
IARIA
,
2019
| |
|
ISBN
|
|
|
|
978-1-61208-725-2
| |
|
Volume/pages
|
|
|
|
p. 11-16
| |
|