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

机译:西方主流媒体对中国问题在线新闻的自动情感分析

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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:结合媒体话语分析研究以及自然语言处理,数据挖掘和信息访问方面的进展,提出了一种西方主流媒体对新闻报道的自动情感分析框架,并进行了初步实验。自动情绪分析系统架构包括:(1)识别中英文等效查询表达; (2)领域和语言知识库的建设; (三)新闻事件的恢复; (4)对新闻文本的情感分析。工作流程包括两个阶段,即用于实时处理的资源的离线构建(例如可比较的或并行的语料库和领域知识库)以及通过机器学习和数据挖掘技术对新闻文本进行的在线分析。所提出的方法可以快速响应从海外媒体收集到的各种信息,并为例如政府制定有效的决策程序。

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