An analysis of affective expressions in articles of popular science by text mining

Kuei Chen Chiu, Chun Lin Liu, Ruey Lin Chen

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

This paper aims to analyze affective expressions in articles of popular science by text mining with the keywords Cancer and Immunity. This study selects 145 articles from the website of a magazine and segmented them into 410,919 terms. And the study uses an automatic system to classify the terms into vocabulary categories, selecting the affective terms with specific vocabulary categories. The results show those the affective terms in the analyzed articles of popular science are not significantly differential with year and decade. But there is a significantly negative correlation with the quantity of articles that are published in the same year. That is, the more articles are published the less proportion of affective terms to the summary terms occurs on the articles.

原文English
主出版物標題IEEM 2015 - 2015 IEEE International Conference on Industrial Engineering and Engineering Management
發行者IEEE Computer Society
頁面966-970
頁數5
ISBN(電子)9781467380669
DOIs
出版狀態Published - 2016 一月 18
事件IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2015 - Singapore, Singapore
持續時間: 2015 十二月 62015 十二月 9

出版系列

名字IEEE International Conference on Industrial Engineering and Engineering Management
2016-January
ISSN(列印)2157-3611
ISSN(電子)2157-362X

Conference

ConferenceIEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2015
國家Singapore
城市Singapore
期間15-12-0615-12-09

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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