IDEAS home Printed from https://ideas.repec.org/p/egu/wpaper/2043.html
   My bibliography  Save this paper

Improvement on the association strength: implementing a probabilistic measure based on combinations without repetition

Author

Listed:
  • Mathieu P.A. Steijn

Abstract

The use of co-occurrence data is common in various domains. Co-occurrence data often needs to be normalised to correct for the size-e↵ect. To this end, van Eck and Waltman (2009) recommend a probabilistic measure known as the association strength. However, this formula is based on combinations with repetition, even though in most uses self-co-occurrences are non-existent or irrelevant. A more accurate measure based on combinations without repetition is introduced here and compared to the original formula in mathematical derivations, simulations, and patent data, which shows that the original formula overestimates the relation between a pair and that some pairs are disproportionally more overestimated than others. The new measure is available in the EconGeo package for R by Balland (2016).

Suggested Citation

  • Mathieu P.A. Steijn, 2020. "Improvement on the association strength: implementing a probabilistic measure based on combinations without repetition," Papers in Evolutionary Economic Geography (PEEG) 2043, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Sep 2020.
    • Handle: RePEc:egu:wpaper:2043
    as

    Download full text from publisher

    File URL: http://econ.geo.uu.nl/peeg/peeg2043.pdf
    File Function: Version September 2020
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pierre-Alexandre Balland & David Rigby & Ron Boschma, 2015. "The technological resilience of US cities," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 8(2), pages 167-184.
    2. Ron Boschma & Pierre-Alexandre Balland & Dieter Franz Kogler, 2015. "Relatedness and technological change in cities: the rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 24(1), pages 223-250.
    3. 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.
    4. Frank Neffke & Martin Henning & Ron Boschma & Karl-Johan Lundquist & Lars-Olof Olander, 2011. "The Dynamics of Agglomeration Externalities along the Life Cycle of Industries," Regional Studies, Taylor & Francis Journals, vol. 45(1), pages 49-65.
    5. Hoekman, Jarno & Frenken, Koen & Tijssen, Robert J.W., 2010. "Research collaboration at a distance: Changing spatial patterns of scientific collaboration within Europe," Research Policy, Elsevier, vol. 39(5), pages 662-673, June.
    6. Waltman, Ludo & van Eck, Nees Jan & Noyons, Ed C.M., 2010. "A unified approach to mapping and clustering of bibliometric networks," Journal of Informetrics, Elsevier, vol. 4(4), pages 629-635.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    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. Mathieu P A Steijn & Pierre-Alexandre Balland & Ron Boschma & David L Rigby, 2023. "Technological diversification of U.S. cities during the great historical crises," Journal of Economic Geography, Oxford University Press, vol. 23(6), pages 1303-1344.
    2. Pierre-Alexandre Balland & Ron Boschma & Joan Crespo & David L. Rigby, 2017. "Smart Specialization policy in the EU: Relatedness, Knowledge Complexity and Regional Diversification," Papers in Evolutionary Economic Geography (PEEG) 1717, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2017.
    3. María Pinto & Rosaura Fernández-Pascual & David Caballero-Mariscal & Dora Sales, 2020. "Information literacy trends in higher education (2006–2019): visualizing the emerging field of mobile information literacy," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1479-1510, August.
    4. Lilian Cervo Cabrera & Carlos Eduardo Caldarelli & Marcia Regina Gabardo Camara, 2020. "Mapping collaboration in international coffee certification research," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2597-2618, September.
    5. Duygu Buyukyazici & Leonardo Mazzoni & Massimo Riccaboni & Francesco Serti, 2024. "Workplace skills as regional capabilities: relatedness, complexity and industrial diversification of regions," Regional Studies, Taylor & Francis Journals, vol. 58(3), pages 469-489, March.
    6. Evi Sachini & Nikolaos Karampekios & Pierpaolo Brutti & Konstantinos Sioumalas-Christodoulou, 2020. "Should I stay or should I go? Using bibliometrics to identify the international mobility of highly educated Greek manpower," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 641-663, October.
    7. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    8. Valentina Di Iasio & Ernest Miguelez, 2022. "The ties that bind and transform: knowledge remittances, relatedness and the direction of technical change [Brain drain or brain bank? The impact of skilled emigration on poor-country innovation]," Journal of Economic Geography, Oxford University Press, vol. 22(2), pages 423-448.
    9. Dieter F. Kogler & Jürgen Essletzbichler & David L. Rigby, 2017. "The evolution of specialization in the EU15 knowledge space," Journal of Economic Geography, Oxford University Press, vol. 17(2), pages 345-373.
    10. Matias Nehuen Iglesias, 2021. "The Overlooked Insights from Correlation Structures in Economic Geography," Papers in Evolutionary Economic Geography (PEEG) 2105, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jan 2021.
    11. Jiang, Chenming & Bhat, Chandra R. & Lam, William H.K., 2020. "A bibliometric overview of Transportation Research Part B: Methodological in the past forty years (1979–2019)," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 268-291.
    12. Teresa Farinha & Pierre-Alexandre Balland & Andrea Morrison & Ron Boschma, 2019. "What drives the geography of jobs in the US? Unpacking relatedness," Industry and Innovation, Taylor & Francis Journals, vol. 26(9), pages 988-1022, October.
    13. Dzikowski, Piotr, 2018. "A bibliometric analysis of born global firms," Journal of Business Research, Elsevier, vol. 85(C), pages 281-294.
    14. Jason Deegan & Tom Broekel & Rune Dahl Fitjar, 2021. "Searching through the Haystack:The Relatedness and Complexity of Priorities in Smart Specialization Strategies," Economic Geography, Taylor & Francis Journals, vol. 97(5), pages 497-520, October.
    15. E. Sachini & K. Sioumalas-Christodoulou & C. Chrysomallidis & G. Siganos & N. Bouras & N. Karampekios, 2021. "COVID-19 enabled co-authoring networks: a country-case analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5225-5244, June.
    16. Petralia, Sergio & Balland, Pierre-Alexandre & Morrison, Andrea, 2017. "Climbing the ladder of technological development," Research Policy, Elsevier, vol. 46(5), pages 956-969.
    17. Ron Boschma, 2015. "Towards an Evolutionary Perspective on Regional Resilience," Regional Studies, Taylor & Francis Journals, vol. 49(5), pages 733-751, May.
    18. Philipp Korom, 2019. "A bibliometric visualization of the economics and sociology of wealth inequality: a world apart?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 849-868, March.
    19. María de la Cruz del Río-Rama & Claudia Patricia Maldonado-Erazo & José Álvarez-García & Amador Durán-Sánchez, 2020. "Cultural and Natural Resources in Tourism Island: Bibliometric Mapping," Sustainability, MDPI, vol. 12(2), pages 1-26, January.
    20. Juntao Zheng & Niancai Liu, 2015. "Mapping of important international academic awards," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 763-791, September.

    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:egu:wpaper:2043. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/deguunl.html .

    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.