Lean Based and Artificial Intelligence Powered Support Framework for Independent Screen Entertainment Creators

  • Ivan Spajic Buturac
  • Leo MrsicEmail author
  • Mislav Balkovic
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1178)


Our research is focused in helping new entrants into online comedy business and propose a solution that would enable them to enter a “virtuous cycle of success” very early on using digital technologies. We focus on these independent creators as they represent an enormous potential in future of the industry. Named, screen entertainment, term refers to audiovisual entertainment formats that were traditionally represented by movies and TV series, but have since gone through a transformation in the era of online entertainment, where format boundaries have become blurred. As part of our research, we are using many learnings from traditional movie and TV, acknowledging that the online screen entertainment is much more fluid and diverse. In paper, we first present the problem and run an overview of industry history in order to highlight existing business models and challenges they represent. Next, we provide an overview of existing methods already used in screen entertainment industries. Then, based on all the learnings we aim to propose solution most beneficial to independent creators. Our concept is inspired by Lean methodology, in which we approach early stage comedy in a similar fashion one might approach early stage startup companies using the Lean methodology: by introducing content with just enough features (or qualities) to analyze and test the market potential very early in the process.


Lean methodology Screen entertainment Online video creators Advanced analytics Video content analysis Test screening 


  1. 1.
    Agarwal, A., Balasubramanian, S., Zheng, J., Dash, S.: Parsing screenplays for extracting social networks from movies (2014).
  2. 2.
    An Important Note About Funny Or Die, From The Folks At Funny Or Die - Funny Or Die (n.d.). Accessed 5 May 2019
  3. 3.
    Arnold, M.: Think pink: the story of DePatie-Freleng. BearManor Media, Albany (2015)Google Scholar
  4. 4.
    As algorithms take over, YouTube’s recommendations highlight a human problem (n.d.). Accessed 5 May 2019
  5. 5.
    Booker, C.: The seven basic plots : why we tell stories. Continuum (2004).
  6. 6.
    Cai, Q., Chen, S., White, S.J., Scott, S.K.: Modulation of humor ratings of bad jokes by other people’s laughter. Curr. Biol. CB 29(14), R677–R678 (2019). Scholar
  7. 7.
    Caiani, M., della Porta, D., Wagemann, C.: Mobilizing on the Extreme Right Germany, Italy, and the United States. Oxford University Press (2012).
  8. 8.
    Chaffee, J., Crick, O.: The Routledge Companion to Commedia dell’Arte. Routledge, Abingdon (2017)Google Scholar
  9. 9.
    Covington, P., Adams, J.: Deep Neural Networks for YouTube Recommendations.
  10. 10.
  11. 11.
    Digital 2019: Global Digital Overview—DataReportal – Global Digital Insights (n.d.). Accessed 11 October 2019
  12. 12.
    DNA’s Comedy Lab | Comedy Lab (n.d.). Accessed 5 October 2019
  13. 13.
    How Does the YouTube Algorithm Work? A Guide to Getting More Views (n.d.). Accessed 4 May 2019
  14. 14.
    Is This the End of the TV Writers’ Room as We Know It? | Vanity Fair (n.d.). Accesses 3 October 2019
  15. 15.
    Margarat Valentine, M., Kulkarni, V.: A model for predicting movie’s performance using online rating and revenue. Int. J. Sci. Eng. Res. 4(9) (2013).
  16. 16.
    Murtagh, F., Ganz, A., McKie, S.: The Structure of Narrative: the Case of Film Scripts. Royal Holloway, University of London (2018).
  17. 17.
    New Changes to YouTube Monetization in 2018 to Better Protect Creators (n.d.). Accesses 5 May 2019
  18. 18.
    Ries, E.: The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses, 1st edn. Crown Business, New York (2011)Google Scholar
  19. 19.
    Shatz, M., Helitzer, M.: Comedy Writing Secrets: The Best-Selling Guide to Writing Funny & Getting Paid for It. Penguin, New York (2016)Google Scholar
  20. 20.
    The 20 types of YouTube videos with most views in the UK (n.d.). Accesses 4 May 2019
  21. 21.
  22. 22.
    Why You Must Unlearn What You Know About the YouTube Algorithm (n.d.). Accessed 5 May 2019
  23. 23.
    Why you should have a pre-launch campaign (n.d.). Accessed 5 October 2019

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Algebra University CollegeZagrebCroatia

Personalised recommendations