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Hagiotoponyms in France: Saint popularity, like a herding phase transition

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  • Ausloos, Marcel

Abstract

A spectacular order-order-like transition is presented in the distribution of hagiotoponyms in France. Data analysis and displays distinguish male and female cases. The respective hapax values point to a very large variety of saints with a specific devotion. The most popular ones are St. Martin and the apostles. The less popular ones are not so well known. These features are explained in terms of herding in agent behaviors: people have either preferred popular saints with supposedly good links to God, whence a herding behavior, or (non-herding) agents have preferred to name their local human settlement through a reference to some holy person(s) with more local specificities, - yet with moral or religious leadership, and conjectured to have good contact with God, whence at least locally defined as a saint.

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  • Ausloos, Marcel, 2021. "Hagiotoponyms in France: Saint popularity, like a herding phase transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    • Handle: RePEc:eee:phsmap:v:566:y:2021:i:c:s0378437120309328
    DOI: 10.1016/j.physa.2020.125634
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    References listed on IDEAS

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    1. Ausloos, Marcel, 2016. "Modelling and measuring the irrational behaviour of agents in financial markets: Discovering the psychological solitonAuthor-Name: Dhesi, Gurjeet," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 119-125.
    2. Gurjeet Dhesi & Marcel Ausloos, 2016. "Modelling and Measuring the Irrational behaviour of Agents in Financial Markets: Discovering the Psychological Soliton," Papers 1601.01553, arXiv.org.
    3. Aleksejus Kononovicius & Julius Ruseckas, 2014. "Continuous transition from the extensive to the non-extensive statistics in an agent-based herding model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(8), pages 1-7, August.
    4. Bedeaux, D. & Mazur, P. & Pasmanter, R.A., 1977. "The ballast resistor; An electro-thermal instability in a conducting wire I; The nature of the stationary states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 86(2), pages 355-382.
    5. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    6. Stauffer, Dietrich, 2004. "Introduction to statistical physics outside physics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 1-5.
    7. M. Ausloos, 2013. "A scientometrics law about co-authors and their ranking: the co-author core," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 895-909, June.
    8. Aleksejus Kononovicius & Vygintas Gontis, 2012. "Three-state herding model of the financial markets," Papers 1210.1838, arXiv.org, revised Jan 2013.
    9. Krawczyk, M.J. & Dydejczyk, A. & Kułakowski, K., 2014. "The Simmel effect and babies’ names," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 384-391.
    10. Dietrich Stauffer, 2002. "Percolation And Galam Theory Of Minority Opinion Spreading," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 13(07), pages 975-977.
    11. Dong, Linrong, 2008. "A self-adapting herding model: The agent judge-abilities influence the dynamic behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5868-5873.
    12. Cerqueti, Roy & Ausloos, Marcel, 2015. "Evidence of economic regularities and disparities of Italian regions from aggregated tax income size data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 187-207.
    13. Stauffer, Dietrich, 2000. "Grand unification of exotic statistical physics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(1), pages 121-126.
    14. Vandewalle, N. & Boveroux, Ph. & Minguet, A. & Ausloos, M., 1998. "The crash of October 1987 seen as a phase transition: amplitude and universality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 255(1), pages 201-210.
    15. Frank Schweitzer & Pavlin Mavrodiev & Claudio J. Tessone, 2013. "How Can Social Herding Enhance Cooperation?," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 16(04n05), pages 1-22.
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    2. Rytis Kazakeviv{c}ius & Aleksejus Kononovicius, 2023. "Anomalous diffusion and long-range memory in the scaled voter model," Papers 2301.08088, arXiv.org, revised Feb 2023.

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