A collective Intelligence Based Multi Aspect Sentiment Analysis for Arabic Language

Multi aspect, Text classifications, Sentiment Analysis. Sentiment analysis is one of the most important issues that take place now days, it depends on classifying text files that contain opinions, social network such as (blogs ,facebook, discussion groups,..) participate in increasing the importance of sentiment analysis. Sentiment analysis is used to determine the percentage of approval or refutation based on comments in the files. Although Arabic one of the most rich language and become the first language for more than 24country, studies in sentiment analysis is not enough to show the importance of this issue. This paper presents collective intelligence based multi aspect sentiment analysis for Arabic language. The proposed system depends on a hybrid machine learning algorithms, i.e. Support Vector Machine (SVM), Naive Bays (NB) and Hidden Markove Model (HMM) for Arabic language sentiment analysis. The results show that the proposed system outperforms other systems which use single aspect for sentiment analysis.

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