Analysis of news agencies' descriptive feature by using SVO structure

Shin Ishida, Qiang Ma, Masatoshi Yoshikawa
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引用次数: 1

Abstract

In some sense, news is probably never free from the agencies ' subjective valuation and external forces such as owners and advertisers. As a result, the perspective of news content may be biased. To clarify such a bias, we propose a novel method to extract characteristic descriptions on a certain entity (person, location, organization, etc.) in articles of a news agency. For a given entity, a description is one tuple (called SVO tuple) that consists ofthat entity and the other words or phrases appearing in the same sentence on the basis of their SVO (Subject(S), Verb(V) and Object(O)) roles. By computing the frequency and inverse agency frequency of each description, we extract the characteristic description on a certain entity. Intuitively, a SVO tuple, which is often used by the news agency but not commonly used by the others, has high probability of being of a characteristic description. To validate our method, we carried out an experiment to extract characteristic descriptions on persons by using articles from three well-known Japanese newspaper agencies. The experimental results show that our method can elucidate the different features of each agency's writing style. We discuss the useful application using our method and further work.
用SVO结构分析新闻机构的描述性特征
从某种意义上说,新闻可能永远无法摆脱新闻机构的主观评价和所有者、广告商等外部力量的影响。因此,新闻内容的视角可能会有偏差。为了澄清这种偏见,我们提出了一种新的方法来提取新闻机构文章中关于某个实体(人、地点、组织等)的特征描述。对于给定实体,描述是一个元组(称为SVO元组),该元组由该实体和根据其SVO(主语(S)、动词(V)和宾语(O)角色出现在同一句子中的其他单词或短语组成。通过计算各描述的频率和逆代理频率,提取出某实体上的特征描述。直观地看,新闻机构经常使用而其他机构不常用的SVO元组具有高概率的特征描述。为了验证我们的方法,我们利用日本三家知名报纸机构的文章进行了人物特征描述提取实验。实验结果表明,该方法能较好地阐释各机构写作风格的不同特征。讨论了该方法的应用和进一步的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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