EVALUATION OF 2D AND 3D TECHNIQUES FOR SENTIMENT VISUALIZATION

Abstract

With the rise of user generated content on the Internet, sentiment visualization is being highly researched and practiced. Advances in information visualization, such as the use of three-dimensional visualizations need to be applied to sentiment visualization. However, minimal efforts were taken in the literature, to address when two-dimensional (2D) and three-dimensional (3D) visualization techniques can be used for sentiment visualization. In this thesis, we investigate the 2D and 3D visualization techniques based on the visual variables which represent sentiment in sentiment visualization and perform a comparative empirical study. We conduct a task-based evaluation to measure the performance and cognitive load of visualizations where sentiment is represented by different visual variables in both 2D and 3D visualizations. The objective of this work is to find when 2D and 3D visualization techniques can be used for sentiment visualization and which visual variable is comparatively well-suited for visual representation of sentiment in 2D and 3D. We use scatterplot and bar chart in 2D and 3D for case-study. While the results reflect the known fact that 2D has better performance and lower cognitive load, we investigate different scenarios involving the visual representation of sentiment in 2D and 3D visualizations. Additionally, we discuss the trade-offs of using 2D and 3D visualizations for sentiment visualization. We expect this study to help data analysts, sentiment analysis and visualization researchers and developers make an informed decision of when 3D visualization can be used for sentiment visualization.