VineMap: a metaphor visualization method for public opinion hierarchy from text data - Yajun Cui; Chenhui Li; Chen Chen; Yitao Liang; Yanpeng Hu; Changbo Wang (Journal of Visualization, 2021)
With the growth of hierarchical data in public opinion analysis, new visualization methods that can intuitively present this kind of data are urgently needed. In this paper, we propose VineMap, a new visualization method with a vine metaphor form. Different from other public opinion visualizations, we devote more attention to visualize both the hierarchical structure of texts and the semantic orientation in content. First, we extract a hierarchical topic model from text data. Then we design a visualization based on a vine metaphor form to enable users to understand public opinion in hierarchical form. At the same time, we propose heuristic optimized strategies for the visualization layout. VineMap is applied both on unstructured text data and structured data to demonstrate its applicability. The evaluations not only show users' perceptions to our method but also prove its good performance with respect to generation time, space utilization and visual effect.