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Generation of topic evolution trees from heterogeneous bibliographic networks

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  • Jensen, Scott
  • Liu, Xiaozhong
  • Yu, Yingying
  • Milojevic, Staša

Abstract

The volume of the existing research literature is such it can make it difficult to find highly relevant information and to develop an understanding of how a scientific topic has evolved. Prior research on topic evolution has often leveraged refinements to Latent Dirichlet Allocation (LDA) to identify emerging topics. However, such methods do not answer the question of which studies contributed to the evolution of a topic. In this paper we show that meta-paths over a heterogeneous bibliographic network (consisting of papers, authors and venues) can be used to identify the network elements that made the greatest contributions to a topic. In particular, by adding derived edges that capture the contribution of papers, authors, and venues to a topic (using PageRank algorithm), a restricted meta-path over the bibliographic network can be used to restrict the evolution of topics to the context of interest to a researcher. We use such restricted meta-paths to construct a topic evolution tree that can provide researchers with a web-based visualization of the evolution of a scientific topic in the context of interest to them. Compared to baseline networks without restrictions, we find that restricted networks provide more useful topic evolution trees.

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  • Jensen, Scott & Liu, Xiaozhong & Yu, Yingying & Milojevic, Staša, 2016. "Generation of topic evolution trees from heterogeneous bibliographic networks," Journal of Informetrics, Elsevier, vol. 10(2), pages 606-621.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:2:p:606-621
    DOI: 10.1016/j.joi.2016.04.002
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    as
    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
    2. van Eck, Nees Jan & Waltman, Ludo, 2014. "CitNetExplorer: A new software tool for analyzing and visualizing citation networks," Journal of Informetrics, Elsevier, vol. 8(4), pages 802-823.
    3. Philipp Mayr & Andrea Scharnhorst, 2015. "Scientometrics and information retrieval: weak-links revitalized," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2193-2199, March.
    4. 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.
    5. Ludo Waltman & Nees Eck, 2013. "A smart local moving algorithm for large-scale modularity-based community detection," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(11), pages 1-14, November.
    6. Xiaozhong Liu & Jinsong Zhang & Chun Guo, 2013. "Full‐text citation analysis: A new method to enhance scholarly networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(9), pages 1852-1863, September.
    7. Howard D. White, 2007. "Combining bibliometrics, information retrieval, and relevance theory, Part 2: Some implications for information science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(4), pages 583-605, February.
    8. Anthony F. J. van Raan, 2000. "On Growth, Ageing, and Fractal Differentiation of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 347-362, February.
    9. Eugene Garfield & A. I. Pudovkin & V. S. Istomin, 2003. "Why do we need algorithmic historiography?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(5), pages 400-412, March.
    10. Benjamin F. Jones, 2011. "As Science Evolves, How Can Science Policy?," NBER Chapters, in: Innovation Policy and the Economy, Volume 11, pages 103-131, National Bureau of Economic Research, Inc.
    11. Stephen P. Harter, 1992. "Psychological relevance and information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 43(9), pages 602-615, October.
    12. Dietmar Wolfram, 2015. "The symbiotic relationship between information retrieval and informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2201-2214, March.
    13. Howard D. White, 2015. "Co-cited author retrieval and relevance theory: examples from the humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2275-2299, March.
    14. Marcia J. Bates, 1998. "Indexing and access for digital libraries and the internet: Human, database, and domain factors," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(13), pages 1185-1205.
    15. Lutz Bornmann & Rüdiger Mutz, 2015. "Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2215-2222, November.
    16. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    17. Peter Mutschke & Philipp Mayr, 2015. "Science models for search: a study on combining scholarly information retrieval and scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2323-2345, March.
    18. Xiaozhong Liu & Jinsong Zhang & Chun Guo, 2013. "Full-text citation analysis: A new method to enhance scholarly networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(9), pages 1852-1863, September.
    19. Howard D. White, 2007. "Combining bibliometrics, information retrieval, and relevance theory, Part 1: First examples of a synthesis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(4), pages 536-559, February.
    20. Wagner, Caroline S. & Roessner, J. David & Bobb, Kamau & Klein, Julie Thompson & Boyack, Kevin W. & Keyton, Joann & Rafols, Ismael & Börner, Katy, 2011. "Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature," Journal of Informetrics, Elsevier, vol. 5(1), pages 14-26.
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    4. Qian, Yue & Liu, Yu & Sheng, Quan Z., 2020. "Understanding hierarchical structural evolution in a scientific discipline: A case study of artificial intelligence," Journal of Informetrics, Elsevier, vol. 14(3).

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