The ArtsHumanities and Social Sciences Communications
Identifying gender bias in blockbuster movies through the lens of machine learning
M. J. Haris, A. Upreti, et al.
This innovative study by Muhammad Junaid Haris, Aanchal Upreti, Melih Kurtaran, Filip Ginter, Sebastien Lafond, and Sepinoud Azimi explores gender bias in English blockbuster movies using advanced natural language processing. The authors shed light on how male and female characters are portrayed through emotions, revealing surprising dominance and envy in men, alongside joy in women. Their unique method encourages reflection on gender equality while facilitating automated movie analysis.
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