A Novel Visualization Method for Distinction of Web News Sentiment
A Novel Visualization Method for Distinction of Web News Sentiment
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DOI：
10.1007/978-3-642-04409-0_22
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发表时间：
2009-10
期刊：
影响因子：
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通讯作者：
Jianwei Zhang;Yukiko Kawai;Tadahiko Kumamoto;Katsumi Tanaka
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文献类型：
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作者：
Jianwei Zhang;Yukiko Kawai;Tadahiko Kumamoto;Katsumi Tanaka
最近，越来越多的新闻网站开始提供各种特色服务。然而，对不同新闻来源之间的观点区分进行有效的分析和呈现是有限的。针对新闻记者观点的情感方面，提出了一种基于地图缩放控制的新闻文章情感识别和可视化系统——情感地图。与传统的情绪分析相比，该系统提供了更详细的情绪，而传统的情绪分析只考虑积极和消极的情绪。当用户输入一个或多个查询关键词时，情感地图不仅检索与所关注主题相关的新闻文章，而且还根据特定的地理尺度总结Web新闻的情感趋势。可以根据地图比例尺的变化自动聚合不同级别的情绪。此外，我们考虑了时间方面，并显示了情绪随时间的变化。100人的实验评价表明，该系统具有良好的情感提取精度和可视化效果。
Recently, an increasing number of news websites have come to provide various featured services. However, effective analysis and presentation for distinction of viewpoints among different news sources are limited. We focus on the sentiment aspect of news reporters' viewpoints and propose a system called the Sentiment Map for distinguishing the sentiment of news articles and visualizing it on a geographical map based on map zoom control. The proposed system provides more detailed sentiments than conventional sentiment analysis which only considers positive and negative emotions. When a user enters one or more query keywords, the sentiment map not only retrieves news articles related to the concerned topic, but also summarizes sentiment tendencies of Web news based on specific geographical scales. Sentiments can be automatically aggregated at different levels corresponding to the change of map scales. Furthermore, we take into account the aspect of time, and show the variation in sentiment over time. Experimental evaluations conducted by a total of 100 individuals show the sentiment extraction accuracy and the visualization effect of the proposed system are good.