政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/111622
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    题名: TopicWave: Visual exploration for topics with hierarchical time-varying data
    作者: Hu, Chen-Chi;Xiong, Kai-Wen;Guo, Jian-Kai;Liao, Chun-Min;Chi, Ming-Te
    紀明德
    贡献者: 資訊科學系
    关键词: Information management;Social networking (online);Visualization;Hierarchical data visualizations;Interactive visualization tool;Interactive visualizations;Opinion leaders;Time-varying data visualization;Visual exploration;Visualization technique;Visualization tools;Data visualization
    日期: 2017-01
    上传时间: 2017-08-03 14:12:42 (UTC+8)
    摘要: Opinion leaders have great influence in social networks. When influential events occur, experts may be concerned with the opinion flow of the event from social networks. Therefore, the trend of events during a time interval should be explored using a specific visualization tool. However, designing an intuitive and interactive visualization tool from a time-varying data is still a challenge. For example, major topics are commonly edited by opinion leaders on social networks, and people attracted by opinion leaders join the discussion by commenting on the post. This process is involved in hierarchicallevel commentary, which increases/decreases in volume with time. Nevertheless, exploring commentary properties using traditional visualization techniques is also a challenge for users. In this paper, we propose TopicWave, a visualization tool that combines ThemeRiver Graph (time-varying visualization) and Sunburst (hierarchical data visualization) to visualize the trend of comments on a post in Facebook. TopicWave can also clearly present hierarchy and time-varying trend of comments on a Facebook fan page and provide an intuitive and interactive visualization design. © 2017 ACM.
    關聯: Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017,
    11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017; Beppu; Japan; 5 January 2017 到 7 January 2017; 代碼 126221
    数据类型: conference
    DOI 連結: http://dx.doi.org/10.1145/3022227.3022253
    DOI: 10.1145/3022227.3022253
    显示于类别:[資訊科學系] 會議論文

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