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Using ‘core documents’ for the representation of clusters and topics

Author

Listed:
  • Wolfgang Glänzel

    (K.U. Leuven
    Hungarian Academy of Sciences)

  • Bart Thijs

    (K.U. Leuven)

Abstract

The notion of ‘core documents’, first introduced in the context of co-citation analysis and later re-introduced for bibliographic coupling, refers to the representation of the core of a publication set according to given criteria. In the present study, the notion of core documents is extended to the combination of citation-based and textual links. It is shown that core documents defined this way can be used to represent and describe document clusters and topics at different levels of aggregation. Methodology is illustrated using the example of two ISI Subject Categories selected from applied and social sciences.

Suggested Citation

  • Wolfgang Glänzel & Bart Thijs, 2011. "Using ‘core documents’ for the representation of clusters and topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 297-309, July.
    • Handle: RePEc:spr:scient:v:88:y:2011:i:1:d:10.1007_s11192-011-0347-4
    DOI: 10.1007/s11192-011-0347-4
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    References listed on IDEAS

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    1. Lin Zhang & Wolfgang Glänzel & Liming Liang, 2009. "Tracing the role of individual journals in a cross-citation network based on different indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 821-838, December.
    2. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    3. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
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    Citations

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    Cited by:

    1. Bart Thijs & Lin Zhang & Wolfgang Glänzel, 2015. "Bibliographic coupling and hierarchical clustering for the validation and improvement of subject-classification schemes," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1453-1467, December.
    2. Dahui Dong & Meng-Lin Chen, 2015. "Publication trends and co-citation mapping of translation studies between 2000 and 2015," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 1111-1128, November.
    3. Sameer Kumar & Jariah Mohd. Jan, 2014. "Research collaboration networks of two OIC nations: comparative study between Turkey and Malaysia in the field of ‘Energy Fuels’, 2009–2011," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 387-414, January.
    4. Erjia Yan, 2014. "Topic-based Pagerank: toward a topic-level scientific evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 407-437, August.
    5. Mu-Hsuan Huang & Ssu-Han Chen & Chia-Ying Lin & Dar-Zen Chen, 2014. "Exploring temporal relationships between scientific and technical fronts: a case of biotechnology field," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1085-1100, February.
    6. Mora, Luca & Deakin, Mark & Reid, Alasdair, 2019. "Combining co-citation clustering and text-based analysis to reveal the main development paths of smart cities," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 56-69.
    7. Wolfgang Glänzel, 2015. "Bibliometrics-aided retrieval: where information retrieval meets scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2215-2222, March.
    8. Appio, Francesco Paolo & Lima, Marcos & Paroutis, Sotirios, 2019. "Understanding Smart Cities: Innovation ecosystems, technological advancements, and societal challenges," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 1-14.
    9. Wolfgang Glänzel & Lin Zhang, 2018. "Scientometric research assessment in the developing world: A tribute to Michael J. Moravcsik from the perspective of the twenty-first century," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1517-1532, June.
    10. Wolfgang Glänzel & Bart Thijs, 2012. "Using ‘core documents’ for detecting and labelling new emerging topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 399-416, May.
    11. Matheus Becker Costa & Leonardo Moraes Aguiar Lima Santos & Jones Luís Schaefer & Ismael Cristofer Baierle & Elpidio Oscar Benitez Nara, 2019. "Industry 4.0 technologies basic network identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 977-994, November.
    12. M. Meyer & D. Libaers & B. Thijs & K. Grant & W. Glänzel & K. Debackere, 2014. "Origin and emergence of entrepreneurship as a research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 473-485, January.
    13. Bart Thijs & Wolfgang Glänzel, 2018. "The contribution of the lexical component in hybrid clustering, the case of four decades of “Scientometrics”," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 21-33, April.
    14. Bart Thijs & Edgar Schiebel & Wolfgang Glänzel, 2013. "Do second-order similarities provide added-value in a hybrid approach?," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 667-677, September.
    15. Wolfgang Glänzel, 2012. "The role of core documents in bibliometric network analysis and their relation with h-type indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 113-123, October.
    16. Mu-Hsuan Huang & Chia-Pin Chang, 2014. "Detecting research fronts in OLED field using bibliographic coupling with sliding window," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1721-1744, March.
    17. Shuo Xu & Junwan Liu & Dongsheng Zhai & Xin An & Zheng Wang & Hongshen Pang, 2018. "Overlapping thematic structures extraction with mixed-membership stochastic blockmodel," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 61-84, October.
    18. Rons, Nadine, 2018. "Bibliometric approximation of a scientific specialty by combining key sources, title words, authors and references," Journal of Informetrics, Elsevier, vol. 12(1), pages 113-132.

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