Feeling Positive About Reopening? New Normal Scenarios From COVID-19 US Reopen Sentiment Analytics

Area of Science:

• Social Sciences
• Computational Social Science
• Public Health

Background:

• The Coronavirus pandemic (COVID-19) presented significant socioeconomic challenges and adverse circumstances.
• The pandemic exacerbated emotional and mental healthcare challenges, leading to extreme sentiments like fear and confusion.
• Effective decision-making and policy development necessitate understanding dominant public sentiment trends.

Purpose of the Study:

• To identify public sentiment during the COVID-19 pandemic, specifically concerning the economic reopening debate.
• To explore potential public sentiment scenarios associated with early versus delayed economic reopening.
• To analyze emotional consequences and volatile sentiments amidst the crisis.

Main Methods:

• Utilized textual analytics methodologies on Twitter data, time-aligned with the COVID-19 reopening debate.
• Employed sentiment polarity analysis to assess public support for divergent economic reopening scenarios.
• Incorporated textual data visualization and statistical validation for robust analysis.

Main Results:

• Analysis of American Twitter user data revealed a predominantly positive public sentiment towards reopening the US economy.
• Identified distinct sentiment trends associated with the push for early economic reopening.
• Quantified public sentiment support for two potential scenarios: early and delayed reopening.

Conclusions:

• Public sentiment data from Twitter indicates more positive than negative support for reopening the US economy.
• Developed a novel sentiment polarity-based public sentiment scenarios (PSS) framework for future crisis analysis.
• Findings offer valuable insights for governmental and corporate leaders to navigate the transition to a 'new normal'.