Using Social Media to Predict the Stock Market Crash and Rebound amid the Pandemic: The Digital ‘Haves’ and ‘Have-mores’

Since the 2019 novel Coronavirus disease (COVID-19) spread across globe, risks brought by pandemic set in and stock markets tumbled worldwide. Amidst bleak economic outlook, investors’ concerns over rapidly through social media but wore out shortly. Similarly, crash only caused a relatively short-lived bear market, which bottomed recovered quickly. Meanwhile, technology stocks have grabbed spotlight as digitally advanced sectors seemed to show resilience this Coronavirus-plagued market. This paper aims examine market sentiments using predict performance before, during after March 2020 crash. In addition, Organisation for Economic Co-operation Development Taxonomy of Sectoral Digital-intensity Framework, we identified that outperformed others sentiment was impacted unfolding pandemic. The daily usable sample 1619 firms from 34 first examined via combination hierarchical clustering shape-based distance measure. then tested against time series price changes augmented vector auto-regression. Results towards significantly differences. More interestingly, is characterized level digital intensity, with most demonstrating negative on research among demonstrate how intensity mitigates effect crisis performance.