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Visual Opinion Analysis of Threaded Discussions

机译:循环讨论的视觉意见分析

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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的类型中构成了一个重要的批量,这些信息类型是许多真实世界应用的宝贵来源。然而,对线程讨论进行全面的意见分析是一个具有挑战性的任务,因为它不仅需要对多级线程结构的意见的聚合,而且还需要有效地探索不同聚合级别的复杂关系的方法。在本文中,我们提出了一种解决这一挑战的视觉分析方法。我们的方法利用了有效的文本分析方法,以提取来自大规模螺纹讨论数据的意见和局部结构,并提供综合可视化,以传达意见和螺纹讨论结构。提供了一套交互工具,以实现意见的交叉级探索。我们通过对现实世界循型讨论数据进行案例研究来证明该方法的有效性和效率。

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