Universiteit Leiden Opleiding Informatica Deep learning for Emotional Analysis
نویسندگان
چکیده
The detection of emotions in textual data lets us discover more about the writer. The automatic detection of emotions is useful in a large amount of applications. Furthermore, new developments in deep learning have made it effective in more domains. This research combines the two areas and explores a deep learning method for emotional analysis. The method is benchmarked against current methods using the ISEAR and a Twitter dataset. The deep learning method shows an improvement of 2% for precision and 1% for recall and F1 score compared to the current state of the art. Our research shows that the new developments in deep learning have made it viable for emotional analysis research.
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