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Experimental comparison of first and second-order similarities in a scientometric context

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Listed:
  • Cristian Colliander

    (Umeå University)

  • Per Ahlgren

    (Umeå University
    Stockholm University)

Abstract

The measurement of similarity between objects plays a role in several scientific areas. In this article, we deal with document–document similarity in a scientometric context. We compare experimentally, using a large dataset, first-order with second-order similarities with respect to the overall quality of partitions of the dataset, where the partitions are obtained on the basis of optimizing weighted modularity. The quality of a partition is defined in terms of textual coherence. The results show that the second-order approach consistently outperforms the first-order approach. Each difference between the two approaches in overall partition quality values is significant at the 0.01 level.

Suggested Citation

  • Cristian Colliander & Per Ahlgren, 2012. "Experimental comparison of first and second-order similarities in a scientometric context," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 675-685, February.
    • Handle: RePEc:spr:scient:v:90:y:2012:i:2:d:10.1007_s11192-011-0491-x
    DOI: 10.1007/s11192-011-0491-x
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    References listed on IDEAS

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    1. Per Ahlgren & Bo Jarneving & Ronald Rousseau, 2003. "Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(6), pages 550-560, April.
    2. Timothy Cribbin, 2011. "Discovering latent topical structure by second‐order similarity analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(6), pages 1188-1207, June.
    3. Leo Egghe, 2010. "On the relation between the association strength and other similarity measures," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1502-1504, July.
    4. 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.
    5. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    6. Nees Jan van Eck & Ludo Waltman, 2009. "How to normalize cooccurrence data? An analysis of some well‐known similarity measures," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(8), pages 1635-1651, August.
    7. Leo Egghe, 2009. "New relations between similarity measures for vectors based on vector norms," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 232-239, February.
    8. 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.
    9. Timothy Cribbin, 2011. "Discovering latent topical structure by second-order similarity analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(6), pages 1188-1207, June.
    10. Ahlgren, Per & Colliander, Cristian, 2009. "Document–document similarity approaches and science mapping: Experimental comparison of five approaches," Journal of Informetrics, Elsevier, vol. 3(1), pages 49-63.
    11. Per Ahlgren & Bo Jarneving, 2008. "Bibliographic coupling, common abstract stems and clustering: A comparison of two document-document similarity approaches in the context of science mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(2), pages 273-290, August.
    12. Patrick Glenisson & Wolfgang Glänzel & Olle Persson, 2005. "Combining full-text analysis and bibliometric indicators. A pilot study," Scientometrics, Springer;Akadémiai Kiadó, vol. 63(1), pages 163-180, March.
    13. Leo Egghe & Loet Leydesdorff, 2009. "The relation between Pearson's correlation coefficient r and Salton's cosine measure," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(5), pages 1027-1036, May.
    14. Peters, H. P. F. & van Raan, A. F. J., 1993. "Co-word-based science maps of chemical engineering. Part I: Representations by direct multidimensional scaling," Research Policy, Elsevier, vol. 22(1), pages 23-45, February.
    15. Leo Egghe, 2010. "Good properties of similarity measures and their complementarity," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(10), pages 2151-2160, October.
    16. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-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.
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    Cited by:

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    3. Yang, Hyeonchae & Jung, Woo-Sung, 2016. "Structural efficiency to manipulate public research institution networks," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 21-32.
    4. Guadalupe Palacios-Núñez & Gabriel Vélez-Cuartas & Juan D. Botero, 2018. "Developmental tendencies in the academic field of intellectual property through the identification of invisible colleges," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1561-1574, June.
    5. Yun, Jinhyuk & Ahn, Sejung & Lee, June Young, 2020. "Return to basics: Clustering of scientific literature using structural information," Journal of Informetrics, Elsevier, vol. 14(4).
    6. Fabian Meyer-Brötz & Edgar Schiebel & Leo Brecht, 2017. "Experimental evaluation of parameter settings in calculation of hybrid similarities: effects of first- and second-order similarity, edge cutting, and weighting factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1307-1325, June.
    7. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    8. Cristian Colliander & Per Ahlgren, 2019. "Comparison of publication-level approaches to ex-post citation normalization," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 283-300, July.
    9. Dejian Yu & Wanru Wang & Shuai Zhang & Wenyu Zhang & Rongyu Liu, 2017. "Hybrid self-optimized clustering model based on citation links and textual features to detect research topics," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-21, October.

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