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Interdisciplinary topics of information science: a study based on the terms interdisciplinarity index series

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Abstract

Interdisciplinarity is increasingly widespread. Many technological frontiers and hotspots are emerging in the intersecting research areas. The existing measurement indexes of interdisciplinarity are mostly based on the co-occurrence of authors, institutions, or references, and most focus on the tendency to interdisciplinarity. This paper introduces a new measurement index entitled topic terms interdisciplinarity (TI) for interdisciplinarity topic mining. Taking Information Science & Library Science (LIS) as a case study, this paper identifies interdisciplinary topics by calculating TI values together with Bet values, term frequency values, and others, and analyzes the evolution of interdisciplinary sciences based on social network analysis and time series analysis. It was found that the intersections of external disciplines and pivots of internal topics for LIS can be identified by the utilization of TI value and Bet values. The research has shown that the TI value can identify interdisciplinary topic terms well, and it will be an efficient indicator for interdisciplinary analysis by being complementary to other methods.

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Acknowledgments

This work in this paper was supported by National Social Science Fund of China (Grant No. 14CTQ033), and West Light Foundation of Chinese Academy of Science (Grant No. Y4C0091001).

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Authors and Affiliations

  1. Chengdu Library of Chinese Academy of Sciences, No. 16, South Section 2, Yihuan Road, Chengdu, 610041, Sichuan, People’s Republic of China

    Haiyun Xu, Ting Guo, Lijie Ru & Shu Fang

  2. University of Chinese Academy of Sciences, Beijing, 100040, People’s Republic of China

    Ting Guo & Lijie Ru

  3. Information Engineering Faculty, Jining Medical University, Rizhao, 276826, Shandong, People’s Republic of China

    Zenghui Yue

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  1. Haiyun Xu
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  2. Ting Guo
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  3. Zenghui Yue
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  4. Lijie Ru
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  5. Shu Fang
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Correspondence to Haiyun Xu.

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Xu, H., Guo, T., Yue, Z. et al. Interdisciplinary topics of information science: a study based on the terms interdisciplinarity index series. Scientometrics 106, 583–601 (2016). https://doi.org/10.1007/s11192-015-1792-2

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