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A Computer-Aided Affective Content Analysis of Nanotechnology Newspaper Articles

机译：纳米技术报纸文章的计算机辅助情感内容分析

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摘要

This paper explores the application of an affective content analysis to a selection of nanotechnology news articles gathered from selected newspapers. Thematic content analyses dominate current efforts to mine large text collections of popular science media; the addition of an affective analysis element can yield useful information to supplement future content analysis efforts. Using Whissell's Dictionary of Affect in Language, the analysis rates news articles gathered over a twenty-two year period for their pleasantness, activeness, and imagery, determining the mean affective tone in each category for the entire collection, four 'content themes' (business, national security, health, and environment), and the change in affective tone over the twenty-two year period these articles represent. Whereas the entire collection analyzed as a whole rates very similarly to the average found for everyday English language use and the 'content themes' show similar results, the change in affective tone over the years has been both significant and striking. A sample of results from three years of the twenty-two year period is then qualitatively explored to demonstrate to the reader the connection between the quantitative results of the Dictionary and the qualitative effect of the article's word use and phrasing. The paper ends with a review of the technique's success, implications for policymaking and public dialogue, and avenues for future use.
机译：本文探讨了情感内容分析在从精选报纸中收集的纳米技术新闻精选中的应用。主题内容分析在当前挖掘流行科学媒体的大量文本资料的努力中占主导地位；添加情感分析元素可以产生有用的信息，以补充将来的内容分析工作。使用Whissell的《语言情感词典》，分析对22年内收集到的新闻文章的愉悦性，活跃性和图像进行评级，确定整个馆藏中每个类别的平均情感基调，四个“内容主题”（商业，国家安全，健康和环境）以及这些文章所代表的22年内的情感语调变化。尽管整个收集的整体分析率与日常英语使用的平均值非常相似，并且“内容主题”显示出相似的结果，但多年来情感语调的变化既显着又引人注目。然后定性地探索了22年中三年的结果样本，以向读者展示《词典》的定量结果与文章的单词使用和措词的定性效果之间的联系。本文以该技术的成功，对政策制定和公众对话的意义以及未来使用的途径作一综述。

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