| Web环境下的科技新闻主题挖掘——以国际极地考察领域为例 |
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| 引用本文： | 孔嘉,邓三鸿,张越,张艺炜.Web环境下的科技新闻主题挖掘——以国际极地考察领域为例[J].科技管理研究,2020,40(17):173-179. |
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| 作者姓名： | 孔嘉 邓三鸿 张越 张艺炜 |
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| 作者单位： | 南京大学信息管理学院;江苏省数据工程与知识服务重点实验室,江苏南京210023;南京大学信息管理学院;江苏省数据工程与知识服务重点实验室,江苏南京210023;南京大学信息管理学院;江苏省数据工程与知识服务重点实验室,江苏南京210023;南京大学信息管理学院;江苏省数据工程与知识服务重点实验室,江苏南京210023 |
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| 基金项目： | 南京大学“十三五”实验教学改革研究重点课题“大数据环境下面向学科竞赛的创新能力培养”(SY201919)；中央高校基本科研业务费专项资金资助(010814370301) |
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| 摘 要： | 提出一种基于LDA主题模型的科技新闻主题分析方法,选取2009—2018年中、澳、英、美4国极地科考新闻数据,从主题类型和主题强度角度进行主题演化分析。在中文新闻中,极地测绘等主题的热度上升,极地冰川科考主题的热度下降;在英文新闻中,热门主题为极地冰川科考与极地海洋科考;其余主题热度相对稳定。研究结果表明,该方法可以有效识别科技新闻主题并揭示其演化趋势,可以有效改善网络环境下科技情报分析的自动化程度。
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| 关 键 词： | 科技新闻 文本挖掘 主题分析 LDA模型 极地考察 |
| 收稿时间： | 2019/10/26 0:00:00 |
| 修稿时间： | 2019/11/20 0:00:00 |
Topic Mining of Science and Technology News in Web Environment: Taking the Field of International Polar Expedition as an Example |
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| Abstract: | Analysis of science and technology news is an important way of scientific and technological information service. The application of text mining technology to topic analysis of science and technology news is helpful to reveal the development trend of science and technology quickly and effectively. This study proposed a topic analysis method of science and technology news based on the LDA model and topic evolution analysis was conducted from the perspective of topic type and topic intensity. From 2009 to 2018, the polar expedition news of China, Australia, the UK and the USA were used as data sources for case analysis. In the Chinese news, the heat of topics like polar geomatics research rose but the heat of the polar glaciology research dropped. In the English news, the popular topics were polar glaciology research and polar oceanography research. The rest topics were relatively stable. The results showed that this method could effectively identify, extract and reveal the evolution trend of topics of science and technology news. It could effectively improve the automation degree of scientific and technological information analysis under the network environment. |
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| Keywords: | Science and technology news Text mining Topic analysis LDA model Polar Expedition |
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