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| Identification of Time Characteristics of Research Fronts in the Light of Five Kinds of Association Strength Indicators |
| Huang Fu, Hou Haiyan, Hu Zhigang |
| Science of Science and Management of Science of Technology Research Institute, Dalian University of Technology, Dalian 116024 |
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Abstract Detection of research fronts is an important field of research in scientometrics, and recognition of time characteristics is an important step of the newness feature in determining research fronts. Based on the co-citation analysis method, five kinds of association strength indicators are used to construct the incidence matrix. The Louvain algorithm is then used to obtain clusters of the research front fields, and the sensitivity of different association strength indicators to the time characteristics recognition of the research front is compared. Through the case studies in the field of scientometrics, we find that the five kinds of association strength indicators have different effects on the identification of the time characteristics of research fronts. The inclusion index performs better in analyzing the final results of time characteristics.
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Received: 15 December 2017
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