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Mapping the evolution of scientific fields based on cross-field authors

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  • Sun, Xiaoling
  • Ding, Kun
  • Lin, Yuan

Abstract

Mapping the evolution of scientific fields has drawn much attention in recent years. Researchers have proposed various methods to describe, explain and predict different aspects of science. Network-based analysis has been widely used for knowledge networks, in order to track the changes of research topics and the spread of scientific ideas. Here we propose a novel approach for mapping the science from the perspective of cross-field authors. Computer science is selected based on its interdisciplinary applications. We build a scientific network consisting of computer science conferences as nodes, and two conferences are linked if there exist authors that published papers on both conferences. The scientific fields are identified by community detection algorithm. The results suggest the proposed method based on author overlaps across fields are effective in mapping the science.

Suggested Citation

  • Sun, Xiaoling & Ding, Kun & Lin, Yuan, 2016. "Mapping the evolution of scientific fields based on cross-field authors," Journal of Informetrics, Elsevier, vol. 10(3), pages 750-761.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:3:p:750-761
    DOI: 10.1016/j.joi.2016.04.016
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    References listed on IDEAS

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    1. Xiaoling Sun & Hongfei Lin & Kan Xu & Kun Ding, 2015. "How we collaborate: characterizing, modeling and predicting scientific collaborations," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 43-60, July.
    2. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    3. Milojević, Staša, 2015. "Quantifying the cognitive extent of science," Journal of Informetrics, Elsevier, vol. 9(4), pages 962-973.
    4. David Chavalarias & Jean-Philippe Cointet, 2013. "Phylomemetic Patterns in Science Evolution—The Rise and Fall of Scientific Fields," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
    5. Loet Leydesdorff & Ismael Rafols & Chaomei Chen, 2013. "Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal–journal citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(12), pages 2573-2586, December.
    6. Boyack, Kevin W. & Klavans, Richard, 2014. "Including cited non-source items in a large-scale map of science: What difference does it make?," Journal of Informetrics, Elsevier, vol. 8(3), pages 569-580.
    7. Chaomei Chen & Fidelia Ibekwe-SanJuan & Jianhua Hou, 2010. "The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1386-1409, July.
    8. Mark Herrera & David C Roberts & Natali Gulbahce, 2010. "Mapping the Evolution of Scientific Fields," PLOS ONE, Public Library of Science, vol. 5(5), pages 1-6, May.
    9. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    10. David Chavalarias & Jean-Philippe Cointet, 2008. "Bottom-up scientific field detection for dynamical and hierarchical science mapping, methodology and case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(1), pages 37-50, April.
    11. Richard Klavans & Kevin W. Boyack, 2006. "Quantitative evaluation of large maps of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 475-499, September.
    12. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    13. Loet Leydesdorff & Stephen Carley & Ismael Rafols, 2013. "Global maps of science based on the new Web-of-Science categories," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 589-593, February.
    14. Leydesdorff, Loet & Rafols, Ismael, 2012. "Interactive overlays: A new method for generating global journal maps from Web-of-Science data," Journal of Informetrics, Elsevier, vol. 6(2), pages 318-332.
    15. Martin Rosvall & Carl T Bergstrom, 2010. "Mapping Change in Large Networks," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-7, January.
    16. van Eck, N.J.P. & Waltman, L., 2009. "VOSviewer: A Computer Program for Bibliometric Mapping," ERIM Report Series Research in Management ERS-2009-005-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    17. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
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    Cited by:

    1. Steffen Wendzel & Cédric Lévy-Bencheton & Luca Caviglione, 2020. "Not all areas are equal: analysis of citations in information security research," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 267-286, January.
    2. Park, Inchae & Yoon, Byungun, 2018. "Technological opportunity discovery for technological convergence based on the prediction of technology knowledge flow in a citation network," Journal of Informetrics, Elsevier, vol. 12(4), pages 1199-1222.
    3. Qikai Cheng & Jiamin Wang & Wei Lu & Yong Huang & Yi Bu, 2020. "Keyword-citation-keyword network: a new perspective of discipline knowledge structure analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1923-1943, September.
    4. Andrea Palmucci & Hao Liao & Andrea Napoletano & Andrea Zaccaria, 2020. "Where is your field going? A machine learning approach to study the relative motion of the domains of physics," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.
    5. Malik Khizar Hayat & Ali Daud, 2017. "Anomaly detection in heterogeneous bibliographic information networks using co-evolution pattern mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 149-175, October.

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