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新闻数据的自动化定量叙事分析

Automating Quantitative Narrative Analysis of News Data
课程网址: http://videolectures.net/wapa2011_sudhahar_quantitative/  
主讲教师: Saatviga Sudhahar
开课单位: 布里斯托尔大学
开课时间: 信息不详。欢迎您在右侧留言补充。
课程语种: 英语
中文简介:
摘要为解决计算社会科学中出现的问题,提出了一种基于文本挖掘和模式分析的大规模定量叙事分析(QNA)工作系统。任务是确定新闻主体中的关键角色,以及他们执行的操作,以便进行进一步的分析。这一步通常是手工完成的,劳动强度很大。然后,我们通过以下方法来描述行动者:研究他们在行动者和行动的整体网络中的地位;研究与它们的某些性质有关的时间序列;生成描述每个参与者的主体/客体偏差的散点图;调查每个参与者最相关的行为类型。1987年至2007年间,《纽约时报》刊登了10万篇关于犯罪的文章,展示了这一系统。举个例子,我们发现男人最常对针对这个人的罪行负责,而妇女和儿童最常是这些罪行的受害者。
课程简介: We present a working system for large scale quantitative narrative analysis (QNA) of news corpora, which includes various recent ideas from text mining and pattern analysis in order to solve a problem arising in computational social sciences. The task is that of identifying the key actors in a body of news, and the actions they perform, so that further analysis can be carried out. This step is normally performed by hand and is very labour intensive. We then characterise the actors by: studying their position in the overall network of actors and actions; studying the time series associated with some of their properties; generating scatter plots describing the subject/object bias of each actor; and investigating the types of actions each actor is most associated with. The system is demonstrated on a set of 100,000 articles about crime appeared on the New York Times between 1987 and 2007. As an example, we find that Men were most commonly responsible for crimes against the person, while Women and Children were most often victims of those crimes.
关 键 词: 计算机科学; 模式识别; 网络分析; 文本挖掘
课程来源: 视频讲座网
最后编审: 2019-10-29:cwx
阅读次数: 51