主题演化视角下的国际情报学研究热点与前沿分析

发布时间：2019-04-07 19:00

【摘要】：探测分析情报学领域的研究热点、前沿,对于专家学者进行科研选题、构建学科知识体系具有重要的意义,但是目前研究中以相对孤立的关键词进行分析预测,难以详细、准确地分析情报学发展趋势。文章以SCI收录的6种情报学核心期刊2010—2015年间所刊载的论文为研究对象,基于主题演化分析方法探测、识别国际情报学研究热点与前沿及其发展趋势;基于简单中心算法识别各个子时期的研究主题,然后通过计算向心度、密度以确定各子时期主题自身以及不同主题之间的内、外关联,进行子时期主题关联分析;然后利用Jaccard系数计算相邻子时期主题相似度,构建主题演化路径,进行主题演化分析,识别国际情报学研究热点与前沿。主题演化分析结果表明:定量与定性分析相结合的趋势进一步加强(协作分析、跨学科分析等);借鉴、改进目前模糊集、粗糙集和神经网络等新兴信息技术提升情报分析的准确性、效率,将会是未来几年国际情报学发展的重要发展方向。
[Abstract]:The research hotspots and frontiers in the field of information science are of great significance for experts and scholars to choose scientific research topics and construct knowledge system of disciplines. However, it is difficult to make detailed analysis and prediction with relatively isolated keywords in the current research. The development trend of information science is analyzed accurately. Taking the papers published in six core journals of information science listed by SCI in 2010-2015 as the research object, this paper explores and identifies the hot spots and frontiers of international information science research and its development trend based on the method of subject evolution analysis. Based on the simple central algorithm, the research topic of each sub-period is identified, and then the sub-period theme correlation analysis is carried out by calculating the concentric degree and density to determine the inner and outer correlation of each sub-period theme as well as the internal and external correlation between different themes. Then Jaccard coefficient is used to calculate the theme similarity of neighboring sub-periods, construct the theme evolution path, analyze the theme evolution, and identify the hot spots and frontiers of international information science research. The results of thematic evolution analysis show that the trend of combination of quantitative and qualitative analysis is further strengthened (collaborative analysis, interdisciplinary analysis, etc.); Using for reference, improving the information technology such as fuzzy set, rough set and neural network to improve the accuracy and efficiency of information analysis will be an important development direction of international information science in the coming years.
【作者单位】：山东理工大学科技信息研究所;
【基金】：国家社会科学基金项目“未来新兴科学研究前沿识别研究”(项目编号:16BTQ083) 教育部人文社会科学青年基金项目“基于引文内容分析的科技创新路径识别研究”(项目编号:16YJC870008)成果之一
【分类号】：G353.1;G350

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