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AuthorAl-Kubaisi, Khalid
AuthorHassaine, Abdelali
AuthorJaoua, Ali
Available date2020-09-24T10:49:25Z
Publication Date2017
Publication NameAdvanced Science Letters
ResourceScopus
URIhttp://dx.doi.org/10.1166/asl.2017.8907
URIhttp://hdl.handle.net/10576/16306
AbstractSentiment Analysis is the extraction of writers feeling from a written manuscript. It aims at predicting the sentiment of a particular text using automated means. There are two main ways to make predictions: (1) lexicon-based techniques; (2) machine learning based techniques. Our paper contributes in the machine learning techniques, which are more accurate. Furthermore, we have adopted a hyper-conceptual method as our primary feature extraction technique. This method extracts the keywords in a hierarchical ordering of importance. Classification is then performed using the Random Forest classifier that predicts the sentiment of each document. We were able to obtain an accuracy of 90% on an comments collected from Al Jazeera News website.
SponsorQatar National Research Fund, QNRF& Qatar Foundation, QF
Languageen
PublisherAmerican Scientific Publishers
SubjectHyper conceptual extraction
Opinion mining
Random forest
Sentiment analysis
Social computing
TitleSentiment analysis of islamic news data using hyper-concepts
TypeArticle
Pagination4560-4564
Issue Number5
Volume Number23
dc.accessType Abstract Only


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