摘要
文章基于WordScore的基本原理和信息政策价值分类整合方法，构建了政策价值TESCO模型及词表，并以工信部和科技部的信息政策为样本，将政策文本进行语词切分，按照语词的价值属性建立“语词-政策价值”映射，从而提取文本的政策价值取向，并确定该文本或该领域的政策价值结构，比较不同领域的政策价值差异。
Taking policy documents as materials, this paper advocated a quantitative analysis method by word frequency calculating. Creating a information policy value model TESCO and its vocabulary, the paper took MIIT and MOST as examples, collected all information policies and divided the policy document into words and words, calculated the word frequency to mining potential rules. Then it mapped the words with value vocabulary, and examined the common values and differences. At last, it gave some advice to both information policy development and analysis methodology acceptance.
出处
《数字图书馆论坛》
2011年第8期61-70,共10页
Digital Library Forum
基金
本文系江苏省高校哲学社会科学基金重点项目“两化融合战略下江苏省信息资源开发利用的战略、思路、模式,途径与政蓑研宄”（项目编号：2010ID00M021）和江苏省教育厅哲学社会科学基金项目“基于概念统计的信息政蓑文本计算与实证”（项目编号：2011SJD870004）项目成果.
