The concept Sentiment means the feeling, behavior, belief or attitude towards something that almost being embedded. sentiment analysis is the process of analyzing, extracting, studying and classifying the various reviews, opinions given by people and human emotions into positive, negative, and neutral. It is considered one of the most significant scientific branches that aims to determine the behavior of speaker, the attitude of writer according to some topic or the overall emotional reacting to website, document, event, interaction, products or services. many users can share every day various opinions on different topics that may be detected or embedded by using micro-blogging which considered a rich resource for sentiment analysis and belief mining, such as Facebook, Twitter, forums, and Blogs. recently, a huge number of posted comments, tweets, and reviews on different social media websites include rich information in addition to most online shopping sites provide the opportunity for customers to write reviews about products in order to enhance the sales of those products and to improve both product quality and customer satisfaction. Manual analysis of these large reviews is practically impossible, thus it is needed to discover an automated approach to solve such hard process. In the Middle East and particularly in the Arab world, social media websites continue to be the top-visited websites especially with the current social and political changes in this part of the world. The main objective of this research is to differentiate between various algorithms and techniques of sentiment analysis and classification dependent on the Arabic language, as few studies discuss this point relevant to the Arabic language. Different algorithms and techniques of data mining such as Support Vector Machine (SVM), Naïve Bayes (NB), Bayesian Network (BN), Decision tree (DT), k-nearest neighbor (KNN), Maximum Entropy (ME), and Neural Network (NN) in addition to many other alternative techniques which are used for analyzing and classifying textual data. For the reasons of difficulties in analyzing and mining large number of linguistic words for their. Those techniques are estimated based on Arabic language due to its richness and diversity. The comparison between data mining techniques showed that the most accurate technique is the support vector machine (SVM) algorithm.