Sentiment Analysis on Arabic Content in Social Media: Hybrid Model of Dictionary Based and Fuzzy Logic

Abstract

In recent years, social networks become an information goldmine provides analyzes and inferences rich environment which can be exploited for the development of knowledge in various fields. Several algorithms used to reach the maximum possible accuracy in the semantic analysis of social networks; the most accurate results obtained by using the dictionary based and the fuzzy logic algorithms. In this paper, we worked to obtain better results by creating a hybrid system that fuses the dictionary based and the fuzzy logic to obtain better results rather than using each one of them independently. We end with a prototype that calculates the polarities of the collected sentences and classifies them into seven categories, which are Very Positive, Positive, Good, Neutral, Not Good, Negative, and Very Negative in continuous learning manner, the prototype is learning from the previously collected data, and changes its previous classifications, which proved in the results mathematically.