IDEAS home Printed from https://ideas.repec.org/a/spr/minsoc/v7y2008i1p65-76.html
   My bibliography  Save this article

Language learning, power laws, and sexual selection

Author

Listed:
  • Ted Briscoe

Abstract

No abstract is available for this item.

Suggested Citation

  • Ted Briscoe, 2008. "Language learning, power laws, and sexual selection," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 7(1), pages 65-76, June.
  • Handle: RePEc:spr:minsoc:v:7:y:2008:i:1:p:65-76
    DOI: 10.1007/s11299-007-0040-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11299-007-0040-8
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11299-007-0040-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ramon Ferrer i Cancho & Ricard V. Solé, 2001. "The Small-World of Human Language," Working Papers 01-03-016, Santa Fe Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mehri, Ali & Jamaati, Maryam, 2021. "Statistical metrics for languages classification: A case study of the Bible translations," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).

    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. Diego R Amancio, 2015. "Probing the Topological Properties of Complex Networks Modeling Short Written Texts," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-17, February.
    2. Li, Jianyu & Zhou, Jie, 2007. "Chinese character structure analysis based on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 629-638.
    3. Xiao, Wenjun & Liu, Yanxia & Chen, Guanrong, 2014. "Characterizing vertex-degree sequences in scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 291-295.
    4. Liu, Yanyan & Li, Keping & Yan, Dongyang & Gu, Shuang, 2022. "A network-based CNN model to identify the hidden information in text data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    5. Cui, Xue-Mei & Yoon, Chang No & Youn, Hyejin & Lee, Sang Hoon & Jung, Jean S. & Han, Seung Kee, 2017. "Dynamic burstiness of word-occurrence and network modularity in textbook systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 103-110.
    6. Sheng, Long & Li, Chunguang, 2009. "English and Chinese languages as weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2561-2570.
    7. Camilo Akimushkin & Diego Raphael Amancio & Osvaldo Novais Oliveira Jr., 2017. "Text Authorship Identified Using the Dynamics of Word Co-Occurrence Networks," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-15, January.
    8. STANKOVA, Marija & MARTENS, David & PROVOST, Foster, 2015. "Classification over bipartite graphs through projection," Working Papers 2015001, University of Antwerp, Faculty of Business and Economics.
    9. Tsonis, A.A. & Roebber, P.J., 2004. "The architecture of the climate network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 497-504.
    10. Petralia, Sergio & Kemeny, Thomas & Storper, Michael, 2023. "The transformative effects of tacit technological knowledge," LSE Research Online Documents on Economics 120154, London School of Economics and Political Science, LSE Library.
    11. Ghosh, Dipak & Chakraborty, Sayantan & Samanta, Shukla, 2019. "Study of translational effect in Tagore’s Gitanjali using Chaos based Multifractal analysis technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1343-1354.
    12. Woon Peng Goh & Kang-Kwong Luke & Siew Ann Cheong, 2018. "Functional shortcuts in language co-occurrence networks," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-18, September.
    13. Xiao, Wenjun & Lin, Longxin & Chen, Guanrong, 2015. "Vertex-degree sequences in complex networks: New characteristics and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 437-441.

    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:spr:minsoc:v:7:y:2008:i:1:p:65-76. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.