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

Abstract

The Coronavirus pandemic has created complex challenges and adverse circumstances. This research identifies public sentiment amidst problematic socioeconomic consequences of the lockdown, and explores ensuing four potential public sentiment associated scenarios. The severity and brutality of COVID-19 have led to the development of extreme feelings, and emotional and mental healthcare challenges. This research focuses on emotional consequences-the presence of extreme fear, confusion and volatile sentiments, mixed along with trust and anticipation. It is necessary to gauge dominant public sentiment trends for effective decisions and policies. This study analyzes public sentiment using Twitter Data, timealigned to the COVID-19 reopening debate, to identify dominant sentiment trends associated with the push to reopen the economy. Present research uses textual analytics methodologies to analyze public sentiment support for two potential divergent scenarios-an early opening and a delayed opening, and consequences of each. Present research concludes on the basis of textual data analytics, including textual data visualization and statistical validation, that tweets data from American Twitter users shows more positive sentiment support, than negative, for reopening the US economy. This research develops a novel sentiment polarity based public sentiment scenarios (PSS) framework, which will remain useful for future crises analysis, well beyond COVID-19. With additional validation, this research stream could present valuable time sensitive opportunities for state governments, the federal government, corporations and societal leaders to guide local and regional communities, and the nation into a successful new normal future. INDEX TERMS COVID-19, Coronavirus, feeling, reopen, textual analytics, sentiment analysis, Twitter, new normal I. INTRODUCTION T HE anxiety, stress, financial strife, grief, and general uncertainty of this time will undoubtedly lead to behavioral health crises.-Coe and Enomoto, McKinsey, on the COVID-19 crisis [1]. COVID-19 has become a paradigm shifting phenomenon across domains and disciplines, affecting billions of people worldwide, directly or indirectly. The current COVID-19 pandemic disaster has led to escalating emotional, mental health, and economic issues with significant consequences, and this presents a serious challenge to reopening and recovery initiatives [2]-[4]. Based on the classification of novel coronaviruses (nCoV), the 2019-2020 novel coronavirus is officially termed "Severe acute respiratory syndrome coronavirus 2", also called as "SARS-CoV-2" and "2019-nCoV"". The present study uses SCoV2 (short for SARS-CoV-2) to represent the virus, and COVID-19 to represent the resulting disease [5]. In the United States (US) alone, as of June 24, 2020, COVID-19 has infected well over 3.8 million people and has taken over 142,000 lives, and continues to spread and claim more lives [6]. Moreover, as a result of the "Lockdown"

Socioeconomic factors analysis for COVID-19 US reopening sentiment with Twitter and census data

“…This study uses Twitter data collected between April 30, 2020, and May 08, 2020, to understand the sentiment of the people towards the reopening of the US economy [8] . A total of 293,597 tweets with 90 variables were downloaded using the keyword “reopen”.…”

“…N-gram techniques tokenize texts into single words (unigrams), sequences of two words (bigrams), three words (trigrams), and so on to maintain the order of words and syntactical properties [56] . The findings of the exploratory analysis using steps and processes described above helped to gain a clearer understanding of public perspectives on reopening [8] . After data exploration, sentiment score was generated for each tweet by using the R package sentimentr, and sentiments were classified into positive, negative, and neutral based on matching keywords, word sequences, and prewritten lexicons.…”

“…The present research seeks to understand factors that support reopening, expressed through positive sentiment towards reopening. The goal of the present study is to extend past research which has demonstrated the prominence of positive sentiment towards reopening, though there exists a fair amount of negative sentiment as well [8]. Though Twitter data has been intrinsically analyzed extensively and also contextualized to numerous domains, yet past research has not combined recent Twitter data with demographic data to model potential relationships between sentiment classes based on tweets and COVID-19 relevant data [16,17,18].…”

“…COVID-19 is a highly infections and deadly disease with widespread transmission and significant impacts to the human physical, emotional, and mental health. COVID-19 has also had an impact on the economy, and the way society acts and responds on a daily basis [7] , [8] . To control the spread of COVID-19, the federal government declared statewide emergency and state governments implemented a stay-at-home-order, imposed restriction on mass gathering and non-essential movements.…”

“…Past research investigated fear and trust sentiments of the people towards reopening the economy in the US using exploratory textual analytics, textual data visualization, and hypothesis testing techniques [8] . Similarly, past research has also investigated and classified sentiments of the users (e.g., positive, negative) towards an item, situation, and system [7] .…”