A bibliometric analysis to explore sentiment analysis in the domain of social media research

Abstract

Abstract Businesses use sentiment analysis in different ways for generating market or consumer insights to improve their performance. Existing sentiment analysis studies related to social media research have been significant due to the fact of their rapidly growing potential, as this type of analysis of social media content represents immense benefits. It is imperative to explore the need for such analysis to delineate the trend holistically for knowledge landscaping purposes. The study addresses the research gap through a comprehensive bibliometric review of 523 research articles published in the Scopus database (between 2018 and 2022) to discern the performance, content, and thematic analysis. We adopt an automated bibliometric study approach using the R-tool- biblioshiny for generating and presenting outcomes. Finding points on the vital usages of sentiment analysis such as innovation, transparency, and improved efficiency. It also highlights the uniqueness of sentiment analysis for synthesizing social media content to examine various aspects such as the knowledge-domain map that detects author collaboration networks as well as journal relationships.