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 1月 18 |
| 事件 | IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2015 - Singapore, Singapore 持續時間: 2015 12月 6 → 2015 12月 9 |
出版系列
| 名字 | IEEE International Conference on Industrial Engineering and Engineering Management |
|---|---|
| 卷 | 2016-January |
| ISSN（列印） | 2157-3611 |
| ISSN（電子） | 2157-362X |
Conference
| Conference | IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2015 |
|---|---|
| 國家/地區 | Singapore |
| 城市 | Singapore |
| 期間 | 15-12-06 → 15-12-09 |
All Science Journal Classification (ASJC) codes
- 商業、管理和會計（雜項）
- 工業與製造工程
- 安全、風險、可靠性和品質
UN SDG
此研究成果有助於以下永續發展目標
