Gender and Tone in Recorded Economics Presentations: Audio Analysis with Machine Learning
44 Pages Posted: 3 Jan 2023 Last revised: 21 Mar 2023
Date Written: January 1, 2023
Abstract
This paper studies gender and tone in economics presentations using a replicable,
scalable, machine-learning approach. We train a deep convolutional neural network to
impute labels for gender, age, and tone-of-voice. We apply this to recorded presentations
from the 2022 NBER Summer Institute to measure tone at a high-frequency
level. We find that female economists are more likely to speak in a positive tone and
less likely to be spoken to in a positive tone, even by other women. We find that male
economists are significantly more likely to sound angry or stern compared to female
economists.
Keywords: machine learning, audio analysis, gender, seminar dynamics, tone
JEL Classification: A1, C8, C45
Suggested Citation: Suggested Citation