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Similarity measures, author cocitation analysis, and information theory

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  • Loet Leydesdorff

Abstract

The use of Pearson's correlation coefficient in Author Cocitation Analysis was compared with Salton's cosine measure in a number of recent contributions. Unlike the Pearson correlation, the cosine is insensitive to the number of zeros. However, one has the option of applying a logarithmic transformation in correlation analysis. Information calculus is based on both the logarithmic transformation and provides a non‐parametric statistics. Using this methodology, one can cluster a document set in a precise way and express the differences in terms of bits of information. The algorithm is explained and used on the data set, which was made the subject of this discussion.

Suggested Citation

  • Loet Leydesdorff, 2005. "Similarity measures, author cocitation analysis, and information theory," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(7), pages 769-772, May.
    • Handle: RePEc:bla:jamist:v:56:y:2005:i:7:p:769-772
    DOI: 10.1002/asi.20130
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    1. García-Lillo, Francisco & Seva-Larrosa, Pedro & Sánchez-García, Eduardo, 2023. "What is going on in entrepreneurship research? A bibliometric and SNA analysis," Journal of Business Research, Elsevier, vol. 158(C).
    2. Guerras-Martín, Luis Ángel & Ronda-Pupo, Guillermo Armando & Zúñiga-Vicente, José Ángel & Benito-Osorio, Diana, 2020. "Half a century of research on corporate diversification: A new comprehensive framework," Journal of Business Research, Elsevier, vol. 114(C), pages 124-141.
    3. Zhigao Liu & Yimei Yin & Weidong Liu & Michael Dunford, 2015. "Visualizing the intellectual structure and evolution of innovation systems research: a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 135-158, April.
    4. 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.
    5. Nassiri, Isar & Masoudi-Nejad, Ali & Jalili, Mahdi & Moeini, Ali, 2013. "Normalized Similarity Index: An adjusted index to prioritize article citations," Journal of Informetrics, Elsevier, vol. 7(1), pages 91-98.
    6. Gebauer, Heiko & Saul, Caroline, 2014. "Eine bibliometrische Analyse des Forschungsstandes und der zukünftigen Forschungsfragen für die Transformation vom Produzenten zum Dienstleister," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 68(4), pages 229-249.
    7. Viergutz, Tim & Schulze-Ehlers, Birgit, 2018. "The use of hybrid scientometric clustering for systematic literature reviews in business and economics," DARE Discussion Papers 1804, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).
    8. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    9. Payam Hanafizadeh & Seyedali Marjaie, 2020. "Trends and turning points of banking: a timespan view," Review of Managerial Science, Springer, vol. 14(6), pages 1183-1219, December.
    10. Keilla Dayane Silva-Oliveira & Edson Keyso Miranda Kubo & Michael J. Morley & Rodrigo Médici Cândido, 2021. "Emerging Economy Inward and Outward Foreign Direct Investment: A Bibliometric and Thematic Content Analysis," Management International Review, Springer, vol. 61(5), pages 643-679, October.
    11. Meen Chul Kim & Yoo Kyung Jeong & Min Song, 2014. "Investigating the integrated landscape of the intellectual topology of bioinformatics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 309-335, October.
    12. Shi, Xianwei & Liang, Xingkun & Luo, Yining, 2023. "Unpacking the intellectual structure of ecosystem research in innovation studies," Research Policy, Elsevier, vol. 52(6).
    13. Dzikowski, Piotr, 2018. "A bibliometric analysis of born global firms," Journal of Business Research, Elsevier, vol. 85(C), pages 281-294.
    14. Kerstin Hotte, 2021. "Demand-pull, technology-push, and the direction of technological change," Papers 2104.04813, arXiv.org, revised Jan 2023.
    15. Xin Ying An & Qing Qiang Wu, 2011. "Co-word analysis of the trends in stem cells field based on subject heading weighting," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 133-144, July.
    16. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    17. Zhang, Yucheng & Zhang, Meng & Li, Jing & Liu, Guangjian & Yang, Miles M. & Liu, Siqi, 2021. "A bibliometric review of a decade of research: Big data in business research – Setting a research agenda," Journal of Business Research, Elsevier, vol. 131(C), pages 374-390.
    18. Lu Huang & Xiang Chen & Yi Zhang & Yihe Zhu & Suyi Li & Xingxing Ni, 2021. "Dynamic network analytics for recommending scientific collaborators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 8789-8814, November.
    19. Alesia Zuccala & Peter Besselaar, 2009. "Mapping review networks: Exploring research community roles and contributions," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 111-122, October.
    20. 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).

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