Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles

56 Pages Posted: 7 Jun 2019

See all articles by Prithwiraj Choudhury

Prithwiraj Choudhury

Harvard University - Business School (HBS)

Dan Wang

Columbia Business School - Management

Natalie Carlson

Columbia University - Columbia Business School

Tarun Khanna

Harvard University - Business School (HBS)

Date Written: May 22, 2019

Abstract

We demonstrate how a novel synthesis of three methods — (1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural network algorithm — can shed light on questions related to CEO oral communication. With videos and corresponding transcripts of interviews with emerging market CEOs, we employ this synthesis of methods to discover five distinct communication styles that incorporate both verbal and nonverbal aspects of communication. Our data are comprised of interviews that represent unedited expressions and content, making them especially suitable as data sources for the measurement of an individual’s communication style. We then perform a proof-of-concept analysis, correlating CEO communication styles to M&A outcomes, highlighting the value of combining text and videographic data to define styles. We also discuss the benefits of using our methods versus current research methods.

Keywords: machine learning, topic modeling, facial image recognition, CEO communication, topic entropy

Suggested Citation

Choudhury, Prithwiraj and Wang, Dan and Carlson, Natalie and Khanna, Tarun, Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles (May 22, 2019). Available at SSRN: https://ssrn.com/abstract=3392448 or http://dx.doi.org/10.2139/ssrn.3392448

Prithwiraj Choudhury (Contact Author)

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Morgan 270C
Boston, MA 02163
United States

Dan Wang

Columbia Business School - Management ( email )

3022 Broadway
New York, NY 10027
United States

Natalie Carlson

Columbia University - Columbia Business School ( email )

3022 Broadway
New York, NY 10027
United States

Tarun Khanna

Harvard University - Business School (HBS) ( email )

Soldiers Field Road
Morgan 270C
Boston, MA 02163
United States

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