Nowadays, sentiment analysis is the most prevalent method adopted by many companies to conduct real-time surveys based on the information available on different social media platforms. Sentiments are internal feelings and emotions of a person towards an entity in the real world. Sentiment analysis is a study about capturing the various sentiment information supplied in natural language writings. In the initial years, most of the research was dedicated to extracting sentiment traits through analyzing lexical and syntactic variables. However, as a vast range of disciplines have begun leveraging the potential of machine learning based algorithms for solving different types of problems, consequently, the idea of machine learning is not nascent anymore in the area of sentiment analysis. Many researchers have proved their proficiency in analyzing the opinion of internet users. The current paper also proposes and examines a hybrid approach sentiment representation model to analyze and classify twitter sentiments. The experiment was performed on the popular dataset, i.e., Sentiment140 Twitter dataset. The outcome procured from the proposed model showed significantly better results than the other existing machine learning based models.