IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-019-10213-0.html
   My bibliography  Save this article

Quantifying and predicting success in show business

Author

Listed:
  • Oliver E. Williams

    (Queen Mary University of London)

  • Lucas Lacasa

    (Queen Mary University of London)

  • Vito Latora

    (Queen Mary University of London
    The British Library
    Università di Catania and INFN
    Complexity Science Hub Vienna (CSHV))

Abstract

In certain artistic endeavours—such as acting in films and TV, where unemployment rates hover at around 90%—sustained productivity (simply making a living) is probably a better proxy for quantifying success than high impact. Drawing on a worldwide database, here we study the temporal profiles of activity of actors and actresses. We show that the dynamics of job assignment is well described by a “rich-get-richer” mechanism and we find that, while the percentage of a career spent active is unpredictable, such activity is clustered. Moreover, productivity tends to be higher towards the beginning of a career and there are signals preceding the most productive year. Accordingly, we propose a machine learning method which predicts with 85% accuracy whether this “annus mirabilis” has passed, or if better days are still to come. We analyse actors and actresses separately, also providing compelling evidence of gender bias in show business.

Suggested Citation

  • Oliver E. Williams & Lucas Lacasa & Vito Latora, 2019. "Quantifying and predicting success in show business," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10213-0
    DOI: 10.1038/s41467-019-10213-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-10213-0
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-019-10213-0?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
    ---><---

    Citations

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


    Cited by:

    1. Vitalis, Kyriacos & Stefanidis, Dimosthenis & Pallis, George & Dikaiakos, Marios & Nicolaou, Nicos & Nicolaides, Christos, 2024. "Quantifying the impact of online social networks on the success of entrepreneurs," OSF Preprints x6vda, Center for Open Science.
    2. Giovanni Colavizza, 2022. "Seller-buyer networks in NFT art are driven by preferential ties," Papers 2210.04339, arXiv.org, revised Nov 2022.
    3. Zappalà, Chiara & Biondo, Alessio Emanuele & Pluchino, Alessandro & Rapisarda, Andrea, 2023. "The paradox of talent: How chance affects success in tennis tournaments," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    4. Xiaomei Bai & Fuli Zhang & Jinzhou Li & Zhong Xu & Zeeshan Patoli & Ivan Lee, 2021. "Quantifying scientific collaboration impact by exploiting collaboration-citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7993-8008, September.
    5. Sándor Juhász & Gergő Tóth & Balázs Lengyel, 2020. "Brokering the core and the periphery: Creative success and collaboration networks in the film industry," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-15, February.

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10213-0. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.nature.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.