Predicting New TV Series Ratings from their Pilot Episode Scripts


  •  Starling Hunter    
  •  Susan Smith    
  •  Ravi Chinta    

Abstract

Empirical studies of the determinants of the ratings of new television series have focused almost exclusively on factors known after a decision has been made to broadcast the series. The current study directly addresses this gap in the literature. Specifically, we first develop a parsimonious model to predict the audience size of new television series. We then test our model on a sample of 116 hour-long, scripted television series that debuted on one of the four major US television networks during the 2009-2014 seasons. Our key predictor is the size of the main component of the text network developed from the script of the pilot episode of each series. As expected, this size measure strongly explains the number of viewers of the new series’ first several episodes.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1923-869X
  • ISSN(Online): 1923-8703
  • Started: 2011
  • Frequency: bimonthly

Journal Metrics

Google-based Impact Factor (2021): 1.43

h-index (July 2022): 45

i10-index (July 2022): 283

h5-index (2017-2021): 25

h5-median (2017-2021): 37

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