TY - JOUR
T1 - VineMap
T2 - a metaphor visualization method for public opinion hierarchy from text data
AU - Cui, Yajun
AU - Li, Chenhui
AU - Chen, Chen
AU - Liang, Yitao
AU - Hu, Yanpeng
AU - Wang, Changbo
N1 - Publisher Copyright:
© 2021, The Visualization Society of Japan.
PY - 2021/10
Y1 - 2021/10
N2 - Abstract: 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. Graphic abstract: [Figure not available: see fulltext.]
AB - Abstract: 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. Graphic abstract: [Figure not available: see fulltext.]
KW - Hierarchical topic model
KW - Information visualization
KW - Metaphor design
KW - Public opinion visualization
UR - https://www.scopus.com/pages/publications/85106463107
U2 - 10.1007/s12650-021-00757-z
DO - 10.1007/s12650-021-00757-z
M3 - 文章
AN - SCOPUS:85106463107
SN - 1343-8875
VL - 24
SP - 1097
EP - 1111
JO - Journal of Visualization
JF - Journal of Visualization
IS - 5
ER -