With over 319 million monthly active users, Twitter has developed into a goldmine for organizations and people with a strong political, social, or economic incentive to retain or enhance their clout and reputation. Sentiment analysis enables these firms to conduct real-time surveys on numerous social media platforms. Twitter sentiment analysis technology enables the measurement of public attitudes toward certain events or products. The majority of current research is devoted to extracting sentiment traits through the analysis of lexical and syntactic variables. These characteristics are openly stated using emotional words, emoticons, and exclamation points, among others. In this research, effective feature extraction is accomplished via the use of convolution mapping and an attention layer. These features are then learned by random forest.