A Structural Neural Autopilot Analysis of Social Media Use Around the Pandemic Lockdown

50 Pages Posted: 11 Apr 2024 Last revised: 12 Apr 2024

See all articles by Yi Xin

Yi Xin

California Institute of Technology

Lawrence J. Jin

SC Johnson College of Business, Cornell University; National Bureau of Economic Research (NBER)

Jessica Fong

University of Michigan Ross School of Business

Colin Camerer

California Institute of Technology - Division of the Humanities and Social Sciences

Date Written: March 28, 2024

Abstract

This paper describes and estimates a "neural autopilot" model of habit formation. The estimation uses individual-level data on posting behavior from a Chinese social media platform before, during, and after the 2020 pandemic lockdown. The model produces interpretable parameter estimates about autopilot habit formation. It shows that once habit is neuroscientifically formalized, changes in preferences are no longer required to explain observed behavior change. Moreover, the neural autopilot model fits the data better than a traditional model of habit that uses changing preferences to explain choice persistence. We also find that forced experimentation alone does not lead to persistent habitual postings after the lockdown ends. Counterfactual forecasts, which are derived from simulating behavior using the structural model, show that reducing the volatility in posting rewards, in conjunction with forced experimentation, would significantly increase habitual postings. This finding suggests that higher moments of the reward process may play an important role in creating habits.

Keywords: neural autopilot, habit formation, counterfactual analysis

JEL Classification: D01, D03, D83, G02, M31

Suggested Citation

Xin, Yi and Jin, Lawrence J. and Fong, Jessica and Camerer, Colin F., A Structural Neural Autopilot Analysis of Social Media Use Around the Pandemic Lockdown (March 28, 2024). Available at SSRN: https://ssrn.com/abstract=4757025 or http://dx.doi.org/10.2139/ssrn.4757025

Yi Xin

California Institute of Technology ( email )

Pasadena, CA 91125
United States

Lawrence J. Jin

SC Johnson College of Business, Cornell University ( email )

310E Warren Hall
Ithaca, NY 14850
United States
607-255-0581 (Phone)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Jessica Fong

University of Michigan Ross School of Business ( email )

701 Tappan Ave
Ann Arbor, MI 48109
United States

Colin F. Camerer (Contact Author)

California Institute of Technology - Division of the Humanities and Social Sciences ( email )

1200 East California Blvd.
Pasadena, CA 91125
United States
626-395-4054 (Phone)
626-432-1726 (Fax)

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