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Topic based research competitiveness evaluation

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Abstract

Research competitiveness analysis refers to the measurement, comparison and analysis of the research status (i.e., strength and/or weakness) of different scientific research bodies (e.g., institutions, researchers, etc.) in different research fields. Improving research competitiveness analysis method can be conducive to accurately obtaining the research status of research fields and research bodies. This paper presents a method of evaluating the competitiveness of research institutions based on research topic distribution. The method uses the LDA topic model to obtain a paper-topic distribution matrix to objectively assign the academic impact of papers (such as number of citations) to research topics. Then the method calculates the competitiveness of each research institution on each research topic with the help of an institution-paper matrix. Finally, the competitiveness and the research strength and/or weakness of the institutions are defined and characterized. A case study shows that the method can lead to an objective and effective evaluation of the research competitiveness of research institutions in a given research field.

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Notes

  1. Data retrieval time: Jan. 2017.

  2. https://www.usnews.com/best-graduate-schools/top-science-schools/artificial-intelligence-rankings. http://www.askci.com/news/chanye/20160816/11231254039.shtml. https://www.tech.163.com/photoview/6PGI0009/13525.html.

  3. Actually, in our case study, except documents, we only give a topic number (i.e., 5) to the algorithm to get the result topic distributions.

  4. http://scikit-learn.org/stable/, http://scikit-learn.org/0.16/modules/generated/sklearn.lda.LDA.html.

  5. http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html.

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Acknowledgements

The present study is an extended version of an article (Yue and Ma 2017) presented at the 16th International Conference on Scientometrics and Informetrics, Wuhan (China), 16–20 October 2017. This work is supported by the National Natural Science Foundation of China under Grant (No. 71603252); the Young Talent-Field Frontier Project of Wuhan Documentation and Information Center, Chinese Academy of Sciences.

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Authors and Affiliations

  1. Wuhan Documentation and Information Center, Chinese Academy of Sciences, Wuhan, China

    Tingcan Ma, Ruinan Li, Guiyan Ou & Mingliang Yue

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  1. Tingcan Ma
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  2. Ruinan Li
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  3. Guiyan Ou
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  4. Mingliang Yue
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Correspondence to Mingliang Yue.

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Ma, T., Li, R., Ou, G. et al. Topic based research competitiveness evaluation. Scientometrics 117, 789–803 (2018). https://doi.org/10.1007/s11192-018-2891-7

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