A new modeling approach for Arabic opinion mining recognition

Over recent years, the world has experienced a huge growth in the volume of shared web texts. Its users generate daily a huge volume of comments and reviews related to different aspects of their lives. In general, opinion mining/sentiment analysis refers to the task of identifying positive and negative opinions, emotions and evaluations related to an article, news, products, services, etc [1]. Arabic Opinion mining is conducted in this study using a dataset consisting of 625 Arabic reviews and comments collected from Trip Advisor website. We introduce a new mathematical approach to recognize author's opinion. As the weights computation is determining in the classification, we formulate first a linear program to maximize the distance between the considered classes, then we use these weights to calculate the label of each comment. A further post optimization is also treated to add other contributing descriptors in order to adjust the classification. The results which based on Support Vector Machines showed that the approach is the most influencing on opinion recognition.