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A social voting approach for scientific domain vocabularies construction

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Abstract

Scientific domain vocabularies play an important role in academic communication and lean research management. Confronted with the dramatic increasing of new keywords, the continuous development of a domain vocabulary is important for the domain to keep its long survival in the scientific context. Current methods based either on statistical or linguistic approaches can automatically generate vocabularies that consist of popular keywords, but these approaches fail to capture high-quality standardized terms due to the lack of human intervention. Manual methods take use of human knowledge, but they are both time-consuming and expensive. In order to overcome these deficiencies, this research proposes a novel social voting approach to construct scientific domain vocabularies. It integrates automatic system and human knowledge based on the theory of linguistic arbitrariness and selects widely accepted standardized set of keywords based on social voting. A social voting system has been implemented to aid scientific domain vocabulary construction in the National Natural Science Foundation of China. Two experiments are conducted to demonstrate the effectiveness and validity of the built system. The results show that the constructed domain vocabulary using this system covers a wide range of areas under a discipline and it facilitates the standardization of scientific terminology.

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Notes

  1. The readers can refer to http://www.niso.org/schemas/iso25964.

  2. http://www.researchgate.net.

  3. http://www.scholarmate.com.

  4. http://www.academia.edu.

  5. http://webofknowledge.com.

  6. The readers can refer to “http://www.nsfc.gov.cn/nsfc/cen/daima/index.html”.

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Acknowledgments

This research was partially supported by the General Research Fund of the Hong Kong Research Grant Council (CityU 119611, CityU 148012), the National Natural Science Foundation of China (71371164) and City University of Hong Kong Teaching Development Grant (6000201).

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Authors and Affiliations

  1. School of Management, University of Science and Technology of China, Hefei, Anhui, People’s Republic of China

    Hongbing Jiang & Huaping Chen

  2. Management Engineering School, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China

    Hongbing Jiang

  3. College of Management, Shenzhen University, No. 3688 Nanhai Rd, Shenzhen, Guangdong, People’s Republic of China

    Chen Yang

  4. Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong

    Jian Ma & Thushari Silva

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  1. Hongbing Jiang
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  2. Chen Yang
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  3. Jian Ma
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  4. Thushari Silva
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Correspondence to Chen Yang.

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Jiang, H., Yang, C., Ma, J. et al. A social voting approach for scientific domain vocabularies construction. Scientometrics 108, 803–820 (2016). https://doi.org/10.1007/s11192-016-1990-6

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  • DOI: https://doi.org/10.1007/s11192-016-1990-6

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