Opinion Mining for Arabic Dialects on Twitter.

Opinion Mining (OM) has lately become one of the increasing areas of research identified with text mining and natural language processing. This domain is utilized to detect and extract the sentiment out of text giving valuable and beneficial information related to the author and his/her tendency for a precise topic. The fundamental task is to classify that extracted text which could be a tweet, review, blog, comment, news, etc. to a positive, negative, or neutral sentiment. Most of the instant investigations identified with this topic focus essentially on English textswith a limited and finite assets and resources accessible for miscellaneous languages like Arabic, and its different dialects like the Egyptian dialect, Gulf dialect and so on. This research focus on Arabic Dialects Opinion Mining (ADOM),different Machine Learning (ML) algorithms are applied and the experimental results showthat the Support Vector Machine (SVM) classifier gives the highestand most efficient accuracyof93.56% compared to other applied classifiers. Moreover, this accuracy exceeds the other Arabic related work which makes it very promising and encourages to continuein this line of researchutilizing a normalized dataset with two polarities. [ABSTRACT FROM AUTHOR]