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Analyzing of research patterns based on a temporal tracking and assessing model

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Abstract

Scientific research works conducted by researchers spread all over the world in every research field, which are hard to be tracked and quantified. Although there are many research works focused on scientific community discovery and researcher profiling, it is still a big challenge to track the research patterns and assess the research development for an individual researcher or a research group over time. In this study, we seek to model researchers’ scientific activities and quantify their outcome during their research career. A temporal tracking and assessing model is introduced to represent the research development and quantify the scientific outcome for both an individual and a group along the time. Based on our model, a research topic analyzing approach is developed to extract the topics covered by a research group for the research pattern analysis. Furthermore, a latent research pattern discovering approach is proposed to depict how a research group’s research works contributed by its members are discovered and visualized. The effectiveness of our approach is evaluated based on a real academic dataset.

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Notes

  1. ResearchGate: https://www.researchgate.net/.

  2. http://doc.scrapy.org/en/0.14/faq.html#does-scrapy-crawl-in-breath-first-or-depth-first-order.

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Acknowledgments

The work has been partly supported by Waseda University Grants for Special Research Projects Nos. 2014K-6214, 2015B-381 and 2016B-233, the Hubei Provincial Natural Science Foundation of China under Grant No. 2015CFA010, the National Science Foundation of China under Grant No. 61273232, and the Program for New Century Excellent Talents in University under NCET-13-0785.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, China

    Wei Liang

  2. College of Information Engineering, China Jiliang University, Hangzhou, China

    Qun Jin

  3. Faculty of Human Sciences, Waseda University, Tokorozawa, Japan

    Wei Liang, Qun Jin & Zixian Lu

  4. School of Automation, China University of Geoscience, Wuhan, China

    Min Wu

  5. Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce, Changsha, China

    Wei Liang & Chunhua Hu

Authors
  1. Wei Liang
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  2. Qun Jin
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  3. Zixian Lu
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  4. Min Wu
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  5. Chunhua Hu
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Correspondence to Qun Jin.

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Liang, W., Jin, Q., Lu, Z. et al. Analyzing of research patterns based on a temporal tracking and assessing model. Pers Ubiquit Comput 20, 933–946 (2016). https://doi.org/10.1007/s00779-016-0965-1

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  • DOI: https://doi.org/10.1007/s00779-016-0965-1

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