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Narratives: A visualization to track narrative events as they develop

机译:叙事:在叙事发展过程中跟踪叙事事件的可视化

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Analyzing unstructured text streams can be challenging. One popular approach is to isolate specific themes in the text, and to visualize the connections between them. Some existing systems, like ThemeRiver, provide a temporal view of changes in themes; other systems, like In-Spire, use clustering techniques to help an analyst identify the themes at a single point in time. Narratives combines both of these techniques; it uses a temporal axis to visualize ways that concepts have changed over time, and introduces several methods to explore how those concepts relate to each other. Narratives is designed to help the user place news stories in their historical and social context by understanding how the major topics associated with them have changed over time. Users can relate articles through time by examining the topical keywords that summarize a specific news event. By tracking the attention to a news article in the form of references in social media (such as weblogs), a user discovers both important events and measures the social relevance of these stories.
机译:分析非结构化文本流可能具有挑战性。一种流行的方法是隔离文本中的特定主题,并可视化它们之间的联系。一些现有的系统,例如ThemeRiver,提供了主题更改的时间视图;其他系统(例如In-Spire)使用聚类技术来帮助分析师在单个时间点识别主题。叙事结合了这两种技巧。它使用时间轴来可视化概念随时间变化的方式,并介绍了几种方法来探索这些概念之间的关系。叙事旨在帮助用户了解与新闻相关的主要主题随时间变化的情况,从而将新闻故事置于其历史和社会环境中。通过检查总结特定新闻事件的主题关键字,用户可以通过时间关联文章。通过以社交媒体(例如Weblog)中的引用形式跟踪对新闻报道的关注,用户可以发现重要事件并评估这些故事的社会相关性。

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