Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View
Multimodal visualization of network data is a method considering various types of nodes and visualizing them based on their types, or modes. Compared to traditional network visualization of nodes of the same mode, the new method treats different modes of entities in corresponding ways and presents t...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2015-10-01
|
Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2015/906316 |
id |
doaj-f4b82743c9e94d5d945a9965d9a68e89 |
---|---|
record_format |
Article |
spelling |
doaj-f4b82743c9e94d5d945a9965d9a68e892020-11-25T03:28:29ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-10-011110.1155/2015/906316906316Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered ViewYing TangJia YuChen LiJing FanMultimodal visualization of network data is a method considering various types of nodes and visualizing them based on their types, or modes. Compared to traditional network visualization of nodes of the same mode, the new method treats different modes of entities in corresponding ways and presents the relations between them more clearly. In this paper, we apply the new method to visualize movie network data, a typical multimodal graph data that contains nodes of different types and connections between them. We use an improved force-directed layout algorithm to present the movie persons as the foreground and a density map to present films as the background. By combining the foreground and background, the movie network data are presented in one picture properly. User interactions are provided including detailed pie charts visible/invisible, zooming, and panning. We apply our visualization method to the Chinese movie data from Douban website. In order to testify the effectiveness of our method, we design and perform the user study of which the statistics are analyzed.https://doi.org/10.1155/2015/906316 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ying Tang Jia Yu Chen Li Jing Fan |
spellingShingle |
Ying Tang Jia Yu Chen Li Jing Fan Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View International Journal of Distributed Sensor Networks |
author_facet |
Ying Tang Jia Yu Chen Li Jing Fan |
author_sort |
Ying Tang |
title |
Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View |
title_short |
Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View |
title_full |
Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View |
title_fullStr |
Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View |
title_full_unstemmed |
Visual Analysis of Multimodal Movie Network Data Based on the Double-Layered View |
title_sort |
visual analysis of multimodal movie network data based on the double-layered view |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2015-10-01 |
description |
Multimodal visualization of network data is a method considering various types of nodes and visualizing them based on their types, or modes. Compared to traditional network visualization of nodes of the same mode, the new method treats different modes of entities in corresponding ways and presents the relations between them more clearly. In this paper, we apply the new method to visualize movie network data, a typical multimodal graph data that contains nodes of different types and connections between them. We use an improved force-directed layout algorithm to present the movie persons as the foreground and a density map to present films as the background. By combining the foreground and background, the movie network data are presented in one picture properly. User interactions are provided including detailed pie charts visible/invisible, zooming, and panning. We apply our visualization method to the Chinese movie data from Douban website. In order to testify the effectiveness of our method, we design and perform the user study of which the statistics are analyzed. |
url |
https://doi.org/10.1155/2015/906316 |
work_keys_str_mv |
AT yingtang visualanalysisofmultimodalmovienetworkdatabasedonthedoublelayeredview AT jiayu visualanalysisofmultimodalmovienetworkdatabasedonthedoublelayeredview AT chenli visualanalysisofmultimodalmovienetworkdatabasedonthedoublelayeredview AT jingfan visualanalysisofmultimodalmovienetworkdatabasedonthedoublelayeredview |
_version_ |
1724583942678380544 |