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

Prithwiraj  Choudhury; Dan  Wang; Natalie A. Carlson; Tarun   Khanna

Article | Strategic Management Journal

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

by Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna

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: CEOs; communication style; Machine learning; Spoken Communication; Nonverbal Communication; Personal Characteristics; Analysis; Performance;

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Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Strategic Management Journal 40, no. 11 (November 2019): 1705–1732.

The case explores the strategic decision of global non-profit startup accelerator MassChallenge on whether to pursue a for-profit spinoff, discussing: (1) the costs and benefits of this decision, (2) how best to manage the risks of the decision, and (3) alternative pathways to ensure business sustainability and success.

During the COVID-19 crisis, millions of migrants around the world face food insecurity. This could force migrants to travel during the pandemic, exposing them to health risks and accelerating the spread of the virus. Anecdotal evidence demonstrates the importance of enforcing food security policies to tide the crisis. However, the effects of these policies on containing mobility during the crisis remain unknown. Using mobility data from Facebook, we demonstrate that a policy to guarantee food security that has attracted attention from the Supreme Court of India—portable ration cards—is related to lower mobility during India’s COVID-19 lockdown. Intra-state portable ration cards, which give migrants access to food when they move within their state, are associated with 12% lower intra-state mobility. This effect is particularly strong for states that have fully implemented the policy compared to states that have partially implemented it. However, inter-state portability of ration cards is not related to reduced inter-state mobility, suggesting frictions in implementing the policy across state borders. We also find that food distribution activities by ration shops and civil society actors at the local level are associated with reduced mobility both within states and across state borders. Our study provides generalizable lessons for policymakers around the world: food security policies are essential for helping migrants restrict their travel during the pandemic. Policy implementation requires lead time; therefore, central governments need to coordinate with local actors to increase food distribution to migrants in the immediate term.

Working Paper | HBS Working Paper Series | 2020

Food Security and Human Mobility During the COVID-19 Lockdown

Prithwiraj Choudhury, Wesley W. Koo, Xina Li, Nishant Kishore, Satchit Balsari, Tarun Khanna, Prithwiraj Choudhury, Wesley W. Koo, Xina Li, Nishant Kishore, Satchit Balsari and Tarun Khanna

Keywords: COVID-19; migrants; food security; mobility; Health Pandemics; Food; Distribution; Policy; Global Range;

Citation:

Choudhury, Prithwiraj, Wesley W. Koo, Xina Li, Nishant Kishore, Satchit Balsari, and Tarun Khanna. "Food Security and Human Mobility During the COVID-19 Lockdown." Harvard Business School Working Paper, No. 20-113, May 2020. View Details

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

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