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Emotion Classification in Arabic Poetry using Machine Learning

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 65 - Number 16
Year of Publication: 2013
Authors:
Ouais Alsharif
Deema Alshamaa
Nada Ghneim
10.5120/11006-6300

Ouais Alsharif, Deema Alshamaa and Nada Ghneim. Article: Emotion Classification in Arabic Poetry using Machine Learning. International Journal of Computer Applications 65(16):10-15, March 2013. Full text available. BibTeX

@article{key:article,
	author = {Ouais Alsharif and Deema Alshamaa and Nada Ghneim},
	title = {Article: Emotion Classification in Arabic Poetry using Machine Learning},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {65},
	number = {16},
	pages = {10-15},
	month = {March},
	note = {Full text available}
}

Abstract

In recent years, work on sentiment analysis and automatic text classification in Arabic has seen some progress. However, the problem of emotion classification remains widely under-researched. This work attempts to remedy the situation by considering the problem of classifying documents by their overall sentiment into four affect categories that are present in Arabic poetry- Retha, Ghazal, Fakhr and Heja. This work begins by building an emotional annotated Arabic poetry corpus. The impact of different levels of language preprocessing settings, feature vector dimensions and machine learning algorithms is, then, investigated and evaluated on the emotion classi?cation task.

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