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用于大型活动的视觉辅助反馈工具。

A visual backchannel for large-scale events.

机构信息

University of Calgary.

出版信息

IEEE Trans Vis Comput Graph. 2010 Nov-Dec;16(6):1129-38. doi: 10.1109/TVCG.2010.129.

Abstract

We introduce the concept of a Visual Backchannel as a novel way of following and exploring online conversations about large-scale events. Microblogging communities, such as Twitter, are increasingly used as digital backchannels for timely exchange of brief comments and impressions during political speeches, sport competitions, natural disasters, and other large events. Currently, shared updates are typically displayed in the form of a simple list, making it difficult to get an overview of the fast-paced discussions as it happens in the moment and how it evolves over time. In contrast, our Visual Backchannel design provides an evolving, interactive, and multi-faceted visual overview of large-scale ongoing conversations on Twitter. To visualize a continuously updating information stream, we include visual saliency for what is happening now and what has just happened, set in the context of the evolving conversation. As part of a fully web-based coordinated-view system we introduce Topic Streams, a temporally adjustable stacked graph visualizing topics over time, a People Spiral representing participants and their activity, and an Image Cloud encoding the popularity of event photos by size. Together with a post listing, these mutually linked views support cross-filtering along topics, participants, and time ranges. We discuss our design considerations, in particular with respect to evolving visualizations of dynamically changing data. Initial feedback indicates significant interest and suggests several unanticipated uses.

摘要

我们引入了“可视后信道”(Visual Backchannel)的概念,将其作为一种跟随和探索大规模事件在线对话的新方式。微博客社区(如 Twitter)越来越多地被用作数字后信道,以便在政治演讲、体育比赛、自然灾害和其他大型活动期间及时交流简短的评论和印象。目前,共享更新通常以简单列表的形式显示,这使得难以在事件发生时以及随着时间的推移了解快速发展的讨论的全貌,以及它是如何演变的。相比之下,我们的可视后信道设计提供了一个不断发展的、互动的、多方面的 Twitter 上大规模正在进行的对话的可视概述。为了可视化不断更新的信息流,我们在不断发展的对话背景下,为当前和刚刚发生的事情提供视觉突出显示。作为基于网络的协调视图系统的一部分,我们引入了主题流(Topic Streams),这是一个随时间推移可视化主题的可调整时间堆叠图,一个代表参与者及其活动的人物螺旋(People Spiral),以及一个按大小编码事件照片受欢迎程度的图像云(Image Cloud)。这些相互关联的视图与帖子列表一起,支持沿着主题、参与者和时间范围进行交叉筛选。我们讨论了我们的设计考虑因素,特别是关于动态变化数据的不断演变的可视化。初步反馈表明了极大的兴趣,并提出了一些意想不到的用途。

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