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Related Experiment Video

Updated: Dec 14, 2025

Driving Under the Influence: How Music Listening Affects Driving Behaviors
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Common Laws Driving the Success in Show Business.

Chong Wu1, Zhenan Feng2, Jiangbin Zheng3

  • 1Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong.

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|July 23, 2020
PubMed
Summary
This summary is machine-generated.

Gender bias appears weakly related to success in show business. Deep learning models predict success using common underlying patterns, regardless of actor or actress data. This suggests transferable insights for predicting entertainment industry outcomes.

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Area of Science:

  • Artificial Intelligence
  • Social Science
  • Entertainment Industry Analysis

Background:

  • Understanding factors influencing success in the show business is complex.
  • Investigating potential gender bias in actor/actress career trajectories is crucial.
  • Identifying common success drivers across genders can inform predictive models.

Purpose of the Study:

  • To determine if gender bias impacts success in the show business.
  • To uncover common patterns driving success in the entertainment industry.
  • To develop accurate deep learning models for predicting actor/actress success.

Main Methods:

  • Designed an experiment using gender and productivity as independent variables.
  • Employed deep learning techniques for success prediction and feature extraction.
  • Trained three models: actor data, actress data, and mixed data, compared against benchmarks.

Main Results:

  • Developed deep learning models demonstrating superior generality and accuracy over benchmarks.
  • Observed that models trained on one gender's data performed comparably on the other gender's data.
  • Feature map visualization revealed common learned patterns across differently trained models.

Conclusions:

  • Gender bias appears to have a weak relationship with show business success.
  • Deep learning models can identify transferable success factors irrespective of gender.
  • Findings support the development of more generalized and accurate predictive models for entertainment industry success.