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Automated Sentiment Analysis of Online News on China Issues in Western Mainstream Media

机译:西部主流媒体中中国问题的在线新闻的自动感分析

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Drawing on studies in media discourse analysis and advances in natural language processing, data mining and information access, a framework for automated sentiment analysis of news report from Western mainstream media is proposed and a preliminary experiment is reported in this paper. The automated sentiment analysis system architecture comprises (1) the identification of Chinese-English equivalent query expressions; (2) the construction of domain and linguistic knowledge bases; (3) the recovery of news events; and (4) the sentiment analysis over news texts. The workflow consists of two phases, i.e. an offline construction of resources, such as comparable or parallel corpora and domain knowledge bases, which are utilized in realtime processing, and an online analysis of news texts by means of machine learning and data mining techniques. The proposed methodology leads to a quick response to different information gathered from overseas media and an efficient decision-making procedure for egovernment.
机译:提出了自然语言处理中的媒体话语分析和进步的研究,提出了一种从西部主流媒体的新闻报道自动情绪分析的框架,本文报告了初步实验。自动化情绪分析系统架构包括(1)识别汉英等效查询表达式; (2)域和语言知识库的构建; (3)回收新闻事件; (4)新闻文本的情感分析。工作流程由两个阶段组成,即脱机建设资源,如可比或平行的语料库和域知识库,这些基础是在实时处理中使用的,以及通过机器学习和数据挖掘技术对新闻文本的在线分析。该提出的方法能够快速回应从海外媒体收集的不同信息和egovernment的有效决策程序。

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