|
|
||||||||
The Wharton School, University of Pennsylvania, 3730 Walnut Street, Philadelphia, Pennsylvania 19104
Movie studios often have to choose among thousands of scripts to decide which ones to turn into movies. Despite the huge amount of money at stake, this processknown as green-lighting in the movie industryis largely a guesswork based on experts experience and intuitions. In this paper, we propose a new approach to help studios evaluate scripts that will then lead to more profitable green-lighting decisions. Our approach combines screenwriting domain knowledge, natural-language processing techniques, and statistical learning methods to forecast a movies return on investment (ROI) based only on textual information available in movie scripts. We test our model in a holdout decision task to show that our model is able to significantly improve a studios gross ROI.
The Wharton School, University of Pennsylvania, 3730 Walnut Street, Philadelphia, Pennsylvania 19104
The Wharton School, University of Pennsylvania, 3730 Walnut Street, Philadelphia, Pennsylvania 19104
eliashberg{at}wharton.upenn.edu
kchui{at}wharton.upenn.edu
zjzhang{at}wharton.upenn.edu
History: Received: December 21, 2005;
This article has been cited by other articles:
![]() |
S. K. Hui, J. Eliashberg, and E. I. George Modeling DVD Preorder and Sales: An Optimal Stopping Approach Marketing Science, November 1, 2008; 27(6): 1097 - 1110. [Abstract] [PDF] |
||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |