Visual Opinion Analysis of Threaded Discussions

Online discussion forums make up a significant bulk in the type of opinion information that represents a valuable source for many real-world applications. However, conducting comprehensive opinion analysis of threaded discussions is a challenging task because it requires not only an aggregation of opinions over the multi-level thread structures, but also effective methods for exploring the complex relationships across different aggregated levels. In this paper, we present a visual analysis approach to address this challenge. Our approach leverages efficient text analysis methods to extract opinions and topical structures from massive threaded discussion data, and provides integrated visualizations to convey both opinion and threaded discussion structures. A suite of interaction tools is provided to enable cross-level explorations of opinions. We demonstrate the effectiveness and efficiency of the approach by conducting a case study on a real-world threaded discussion data.