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Visual Opinion Analysis of Threaded Discussions

机译:主题讨论的视觉观点分析

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Online discussion forums make up a significant bulk in the type of opinion information that represents a valuable source for many real-world applications. However, conducting comprehensive opinion analysis of threaded discussions is a challenging task because it requires not only an aggregation of opinions over the multi-level thread structures, but also effective methods for exploring the complex relationships across different aggregated levels. In this paper, we present a visual analysis approach to address this challenge. Our approach leverages efficient text analysis methods to extract opinions and topical structures from massive threaded discussion data, and provides integrated visualizations to convey both opinion and threaded discussion structures. A suite of interaction tools is provided to enable cross-level explorations of opinions. We demonstrate the effectiveness and efficiency of the approach by conducting a case study on a real-world threaded discussion data.
机译:在线讨论论坛在意见信息类型中占了很大的比例,代表了许多实际应用程序的宝贵资源。但是,对多线程讨论进行全面的意见分析是一项艰巨的任务,因为它不仅需要汇总多级线程结构上的意见,而且还需要有效的方法来探索不同汇总级别之间的复杂关系。在本文中,我们提出了一种视觉分析方法来应对这一挑战。我们的方法利用有效的文本分析方法从大量的线程讨论数据中提取意见和主题结构,并提供集成的可视化来传达意见和线程讨论结构。提供了一套交互工具,以实现对观点的跨级别探索。我们通过在现实世界中的线程讨论数据上进行案例研究来证明该方法的有效性和效率。

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