Related Experiment Video
Updated: Jan 3, 2026

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
Published on: February 12, 2015
Predicting the performance of TV series through textual and network analysis: The case of Big Bang Theory
Andrea Fronzetti Colladon1, Maurizio Naldi2,3
1Department of Engineering, University of Perugia, Via G. Durant, 93, 06125 Perugia, Italy.
Abstract:
TV series represent a growing sector of the entertainment industry. Being able to predict their performance allows a broadcasting network to better focus the high investment needed for their preparation. In this paper, we consider a well known TV series-The Big Bang Theory-to identify factors leading to its success. The factors considered are mostly related to the script, such as the characteristics of dialogues (e.g., length, language complexity, sentiment), while the performance is measured by the reviews submitted by viewers (namely the number of reviews as a measure of popularity and the viewers' ratings as a measure of appreciation). Through correlation and regression analysis, two sets of predictors are identified respectively for appreciation and popularity. In particular the episode number, the percentage of male viewers, the language complexity and text length emerge as the best predictors for popularity, while again the percentage of male viewers and the language complexity plus the number of we-words and the concentration of dialogues are the best choice for appreciation.
Related Concept Videos
Regression Toward the Mean
Social Proof
Theory of Attribution II: Kelley's Covariation Theory
Steps in Outbreak Investigation
The Bell Curve
This pattern applies to many human characteristics beyond intelligence, such as height. For example, if you...
Relationship Formation

