Advanced Automatic Lexicon with Sentiment Analysis Algorithms for Arabic Reviews

Abstract

Sentiment analysis is a statistical analysis of people’s attitudes, directions and emotions about a specific domain. The advance of telecommunication networks makes it very important to develop different sentiment analysis algorithms for gathering information of user preferences from multiple specialized sources. The next step is to analyze the polarity of information and finally gain and predict knowledge to anticipate future results. Arabic language has gained much interest in the past few years because of its wide morphological and linguistic terms. In this study, automatic lexicons for both modern standard Arabic and colloquial vocabularies are developed for multi-domain classical and vernacular terms. In addition, new novel sentiment analysis algorithms are presented, developed and implemented for analyzing the polarity of multi-domain datasets and increasing efficiency and flexibility of sentiment lexicons. The sentiment analysis algorithms are used for analyzing datasets based on their intensification weights to increase the performance of lexicon analyzer. The experimental results show high accuracy, precision, recall and F-measure compared with other recent research experiments.