Abstract
The subject of my research is the production of visual information in sentiment analysis. Sentiment analysis uses natural language processing to identify and understand the emotional tone and underlying phenomena in textual data, and visualization is often used as an analytical tool in this context. The discourse around visualization and technological advances mainly focuses on processing more data efficiently and the reproducibility of visualizations.
Few studies acknowledge the constructed nature of data, the problematic rhetoric of instrumentalist visualization, the materiality of new technologies, the user's position in digital interfaces, the integration of complexity, and the potential for alternative visualization methods. Therefore, my research aims to critically investigate the production of visual information in the context of sentiment analysis and explore the possibilities of developing alternative visualizations for analytical purposes.
