Sentiment Analysis in Digital Spaces: An Overview of Reviews

Digital data generated via social media have become a prosperous entity for sentiment analysis researchers seeking to understand individuals’ feelings, attitudes, and emotions. Numerous systematic reviews have synthesized work across diverse contexts, media, methods, and applications; however they rarely address the validity of sentiment analysis methods or critically examine scientific practices. Our overview of 66 reviews comprises 3,131 unique primary studies using sentiment analysis to dissect online digital data. We provide a high-level overview of current applications, methods, outcomes, and common challenges in sentiment analysis research. A bespoke risk of reporting bias (RoRB) framework was designed to assess the transparency, completeness, and consistency of reporting practices within the included systematic reviews, with particular attention to methodological clarity and adherence to reporting standards. We found diverse applications, methods, outcomes, and persistent challenges outlined in the reviews, which we discuss in relation to the validity of sentiment analysis research. Importantly, reporting practices across the reviews were limited or inconsistent, a concern we examine by considering how existing systematic reviews shape understanding of the field and influence subsequent decisions by researchers and practitioners. We also outline how future research can address these issues and highlight their importance across numerous societal applications.