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Development strategy and collaboration preference in S&T of enterprises based on funded papers: a case study of Google

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Abstract

Science funding plays a guiding role in the development direction of scientific innovation. As one of research funding providers, private companies influence the development of science and technology (S&T) through their selective support. Thus, strategy and layout of enterprises in S&T can be revealed by analysing their funded papers. Taking Google as the example, the paper proposes an analytical method of funded papers by the combination of co-word analysis, clusters analysis and social network analysis, so as to explore the scientific strategy and collaboration preference. The total 2162 valid bibliographic records of papers supported by Google from the Thomson Reuters Web of Science are divided into four groups according to discipline clusters using Hierarchical Clustering Algorithm. Social network analysis is conducted to detect communities among keywords and institutions. The results demonstrate that Google shows different funding patterns between traditional research fields and emerging industries. Famous universities are the main funding targets of Google, and the important institutions can be divided into two groups.

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Acknowledgements

This research is funded by the National Social Science Found Major Project of China (18ZDA325), the National Social Science Found Project of China (16BTQ055) and the Fundamental Research Funds for the Central Universities [Independent Research Projects of Wuhan University (Humanities and Social Sciences)].

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Authors and Affiliations

  1. Research Center for China Science Evaluation, Wuhan University, Wuhan, China

    Rongying Zhao, Xinlai Li, Zhisen Liang & Danyang Li

  2. School of Information Management, Wuhan University, Wuhan, China

    Rongying Zhao, Xinlai Li, Zhisen Liang & Danyang Li

  3. Center for Studies of Information Resourses, Wuhan University, Wuhan, China

    Rongying Zhao, Xinlai Li, Zhisen Liang & Danyang Li

Authors
  1. Rongying Zhao
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  2. Xinlai Li
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  3. Zhisen Liang
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  4. Danyang Li
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Corresponding author

Correspondence to Xinlai Li.

Appendix

Appendix

See Tables 6 and 7.

Table 6 Co-occurrence matrix of discipline and article (section)
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Table 7 2-module matrix of institutions and disciplines in cluster 0 (section)
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Zhao, R., Li, X., Liang, Z. et al. Development strategy and collaboration preference in S&T of enterprises based on funded papers: a case study of Google. Scientometrics 121, 323–347 (2019). https://doi.org/10.1007/s11192-019-03182-0

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