IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v10y2016i2p606-621.html
   My bibliography  Save this article

Generation of topic evolution trees from heterogeneous bibliographic networks

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157715302145
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2016.04.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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. 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.
    4. 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.
    5. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    6. Philipp Mayr & Andrea Scharnhorst, 2015. "Scientometrics and information retrieval: weak-links revitalized," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2193-2199, March.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Dietmar Wolfram, 2015. "The symbiotic relationship between information retrieval and informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2201-2214, March.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    2. Sichao Tong & Per Ahlgren, 2017. "Evolution of three Nobel Prize themes and a Nobel snub theme in chemistry: a bibliometric study with focus on international collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 75-90, July.
    3. Wang, Ruby W. & Wei, Shelia X. & Ye, Fred Y., 2021. "Extracting a core structure from heterogeneous information network using h-subnet and meta-path strength," Journal of Informetrics, Elsevier, vol. 15(3).
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juan Pablo Bascur & Suzan Verberne & Nees Jan Eck & Ludo Waltman, 2023. "Academic information retrieval using citation clusters: in-depth evaluation based on systematic reviews," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2895-2921, May.
    2. Keungoui Kim & Dieter F. Kogler & Sira Maliphol, 2024. "Identifying interdisciplinary emergence in the science of science: combination of network analysis and BERTopic," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    3. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    4. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    5. Chaker Jebari & Enrique Herrera-Viedma & Manuel Jesus Cobo, 2021. "The use of citation context to detect the evolution of research topics: a large-scale analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2971-2989, April.
    6. Andreas Thor & Lutz Bornmann & Werner Marx & Rüdiger Mutz, 2018. "Identifying single influential publications in a research field: new analysis opportunities of the CRExplorer," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 591-608, July.
    7. Tosi, Mauro Dalle Lucca & dos Reis, Julio Cesar, 2021. "SciKGraph: A knowledge graph approach to structure a scientific field," Journal of Informetrics, Elsevier, vol. 15(1).
    8. Nees Jan Eck & Ludo Waltman, 2017. "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1053-1070, May.
    9. Zhang, Lei & Kopak, Rick & Freund, Luanne & Rasmussen, Edie, 2011. "Making functional units functional: The role of rhetorical structure in use of scholarly journal articles," International Journal of Information Management, Elsevier, vol. 31(1), pages 21-29.
    10. Massimo Franceschet & Giovanni Colavizza, 2020. "Quantifying the higher-order influence of scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 951-963, November.
    11. Fang Han & Christopher L. Magee, 2018. "Testing the science/technology relationship by analysis of patent citations of scientific papers after decomposition of both science and technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 767-796, August.
    12. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Zhang, Huiling & Pang, Hongshen, 2021. "Multidimensional Scientometric indicators for the detection of emerging research topics," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    13. Philipp Mayr & Andrea Scharnhorst, 2015. "Scientometrics and information retrieval: weak-links revitalized," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2193-2199, March.
    14. Werner Marx & Lutz Bornmann, 2016. "Change of perspective: bibliometrics from the point of view of cited references—a literature overview on approaches to the evaluation of cited references in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1397-1415, November.
    15. Li Zhang & Ming Liu & Bo Wang & Bo Lang & Peng Yang, 2021. "Discovering communities based on mention distance," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1945-1967, March.
    16. Luis Quevedo & Víctor Velasco & José à lvarez & Paula Moreno, 2023. "Mapping Tourism and Global Change: A Bibliometric Analysis (2012-2022)," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 12, March.
    17. Müge Akbulut & Yaşar Tonta & Howard D. White, 2020. "Related records retrieval and pennant retrieval: an exploratory case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 957-987, February.
    18. McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
    19. Tingcan Ma & Ruinan Li & Guiyan Ou & Mingliang Yue, 2018. "Topic based research competitiveness evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 789-803, November.
    20. Natalya Ivanova & Ekaterina Zolotova, 2023. "Landolt Indicator Values in Modern Research: A Review," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:infome:v:10:y:2016:i:2:p:606-621. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.