Sentiment analysis has been rapidly employed for business decision support. New data mining researchers are yet to have an adequate understanding of the various applications of sentiment analysis while utilising social media data. As a result, it is critical to define the data mining and text analytics research trend holistically using existing literature. The study explores sentiment analysis research for its application in transforming social media data and identifies relevant research aspects through a comprehensive bibliometric review of 523 research articles published in the Scopus database (between 2018 and 2022) to discern the content and thematic analysis. Findings suggested that key purposes of the sentiment analysis are mainly related to innovation, transparency, and efficiency. Our review also highlights the distinctiveness of sentiment analysis for synthesising social media information to investigate various features, including the knowledge-domain map that detects author collaboration networks in the past.