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| Research on Lagging Effect of Topic Diffusion Evolution Face to Prediction of Research Front |
| Liu Ziqiang1, 2, Xu Haiyun1, 2, Yue Lixin3, Fang Shu1 |
1. Chengdu Library of Chinese Academy of Sciences, Chengdu 610041;
2. Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100049;
3. School of Information Resource Management, Renmin University of China, Beijing 100872 |
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Abstract There is a lag in the diffusion of topics from fund projects and papers. Exploring the lag effect of the diffusion and evolution of research topics in fund projects and papers will be helpful to the front topic recognition research of multi-source data fusion. First, LDA (latent Dirichlet allocation) model is used to identify research topics contained in fund projects and paper texts, and similarity is used to construct the association between topics; then, the research front topics are detected by the degree of emergence and attention index of the topics, so as to identify the important research front topics. Further, using the autoregressive distribution lag model and the visualization method of topic diffusion evolution path, this paper analyzes the diffusion lag effect of fund projects and academic papers from the perspectives of external quantitative characteristics and internal topic characteristics. A case study was carried out on the fund project and papers data in the field of artificial intelligence (AI) in 2000-2017 in the US. The results showed that the topics in the fund projects and the papers were obviously lagging. The late stagnation for the topics in the fund projects was two years (2.027888 lag phase relation), and when the lag period is over three years, its influence gradually decreases.
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Received: 26 September 2018
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