  The COVID-19 pandemic has posed an unprecedented challenge to individuals
around the globe. To mitigate the spread of the virus, many states in the U.S.
issued lockdown orders to urge their residents to stay at their homes, avoid
get-togethers, and minimize physical interactions. While many offline workers
are experiencing significant challenges performing their duties, digital
technologies have provided ample tools for individuals to continue working and
to maintain their productivity. Although using digital platforms to build
resilience in remote work is effective, other aspects of remote work (beyond
the continuation of work) should also be considered in gauging true resilience.
In this study, we focus on content creators, and investigate how restrictions
in individual's physical environment impact their online content creation
behavior. Exploiting a natural experimental setting wherein four states issued
state-wide lockdown orders on the same day whereas five states never issued a
lockdown order, and using a unique dataset collected from a short video-sharing
social media platform, we study the impact of lockdown orders on content
creators' behaviors in terms of content volume, content novelty, and content
optimism. We combined econometric methods (difference-in-differences
estimations of a matched sample) with machine learning-based natural language
processing to show that on average, compared to the users residing in
non-lockdown states, the users residing in lockdown states create more content
after the lockdown order enforcement. However, we find a decrease in the
novelty level and optimism of the content generated by the latter group. Our
findings have important contributions to the digital resilience literature and
shed light on managers' decision-making process related to the adjustment of
employees' work mode in the long run.
