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Partial orders and measures for language preferences

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  • Leo Egghe
  • Ronald Rousseau

Abstract

Relative own‐language preference depends on two parameters: the publication share of the language, and the self‐citing rate. Openness of language L with respect to language J depends on three parameters: the publication share of language L, the publication share of language J, and the citation share of language J among all citations given by language L. It is shown that the relative own‐language preference and the openness of one language with respect to another one, can be represented by a partial order. This partial order can be represented by a polygonal line (for the relative own‐language preference) or a three‐dimensional solid (for openness), somewhat in the same spirit as the Lorenz curve for concentration and evenness. Any function used to measure relative own‐language preference or openness of one language with respect to another one should at least respect the corresponding partial orders. This is a minimum requirement for such measures. Depending on the use one wants to make of these measures other requirements become necessary. A logarithmic dependence on the language share(s) seems a natural additional requirement. This would correspond with the logarithmic behavior of psychophysical sensations. We give examples of normalized functions satisfying this additional requirement. It is further investigated if openness partial orders can lead to measures for relative own‐language preference. The article ends with some examples related to the language use in some sociological journals.

Suggested Citation

  • Leo Egghe & Ronald Rousseau, 2000. "Partial orders and measures for language preferences," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(12), pages 1123-1130.
  • Handle: RePEc:bla:jamest:v:51:y:2000:i:12:p:1123-1130
    DOI: 10.1002/1097-4571(2000)9999:99993.0.CO;2-4
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    Cited by:

    1. Zaida Chinchilla-Rodríguez & Grisel Zacca-González & Benjamín Vargas-Quesada & Félix Moya-Anegón, 2015. "Latin American scientific output in Public Health: combined analysis using bibliometric, socioeconomic and health indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 609-628, January.
    2. Zaida Chinchilla-Rodríguez & Sandra Miguel & Félix Moya-Anegón, 2015. "What factors affect the visibility of Argentinean publications in humanities and social sciences in Scopus? Some evidence beyond the geographic realm of research," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 789-810, January.
    3. Leo Egghe & Ronald Rousseau, 2004. "How to measure own-group preference? A novel approach to a sociometric problem," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(2), pages 233-252, February.
    4. R. Basurto-Flores & L. Guzmán-Vargas & S. Velasco & A. Medina & A. Calvo Hernandez, 2018. "On entropy research analysis: cross-disciplinary knowledge transfer," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 123-139, October.
    5. Maria Cláudia Cabrini Grácio & Ely Francina Tannuri Oliveira & Zaida Chinchilla-Rodríguez & Henk F. Moed, 2020. "Does corresponding authorship influence scientific impact in collaboration: Brazilian institutions as a case of study," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1349-1369, November.
    6. Ed J. Rinia & Thed N. van Leeuwen & Eppo E. W. Bruins & Hendrik G. van Vuren & Anthony F. J. van Raan, 2002. "Measuring knowledge transfer between fields of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 347-362, July.
    7. Zaida Chinchilla-Rodríguez & Cassidy R Sugimoto & Vincent Larivière, 2019. "Follow the leader: On the relationship between leadership and scholarly impact in international collaborations," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-18, June.

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