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New Normal Scenarios from COVID-19 Reopen Sentiment Analytics Jim Samuel, Md

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New Normal Scenarios from COVID-19 Reopen Sentiment Analytics Jim Samuel, Md medRxiv preprint doi: https://doi.org/10.1101/2020.06.01.20119362; this version posted June 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 1 Feeling Positive About Reopening? New Normal Scenarios from COVID-19 Reopen Sentiment Analytics Jim Samuel, Md. Mokhlesur Rahman, G. G. Md. Nawaz Ali, Member, IEEE, Yana Samuel, Alexander Pelaez, Peter H.J. Chong, Senior Member, IEEE, and Michael Yakubov Abstract—The Coronavirus pandemic has created complex worldwide directly or indirectly. The current Coronavirus challenges and adverse circumstances. This research identifies pandemic disaster has led to escalating emotional, mental public sentiment amidst problematic socioeconomic consequences health, and economic issues with significant consequences, and of the lockdown, and explores ensuing four potential sentiment associated scenarios. The severity and brutality of COVID-19 this presents a serious challenge to reopening and recovery have led to the development of extreme feelings, and emotional initiatives [2]–[4]. In the United States (US) alone, COVID- and mental healthcare challenges. This research focuses on emo- 19 has infected well over 1.25 million people and killed over tional consequences - the presence of extreme fear, confusion and 80,000, and continues to spread and claim more lives [5]. volatile sentiments, mixed along with trust and anticipation. It is Moreover, as a result of the ’Lockdown’ (present research uses necessary to gauge dominant public sentiment trends for effective decisions and policies. This study analyzes public sentiment Lockdown as the term representing the conditions resulting using Twitter Data, time-aligned to the COVID-19 reopening from state and federal government Novel Coronavirus response debate, to identify dominant sentiment trends associated with regulations and advisories restricting government, organiza- the push to ’reopen’ the economy. Present research uses textual tional, personal, travel and business functionalities), over 30 analytics methodologies to analyze public sentiment support for million people lost their jobs along with a multi-trillion dollar two potential divergent scenarios - an early opening and a delayed opening, and consequences of each. Present research economic impact [6]; furthermore these alarming numbers concludes on the basis of exploratory textual analytics and textual are growing everyday. There is tremendous dissatisfaction data visualization, that Tweets data from American Twitter among common people due to the continued physical, material users shows more positive sentiment support, than negative, and mental health challenges presented by the Lockdown, for reopening the US economy. This research develops a novel evidenced by the growing number of protests across the US sentiment polarity based four scenarios framework, which will remain useful for future crisis analysis, well beyond COVID-19. [7]. There appears to be a significant sentiment, and a strong With additional validation, this research stream could present desire in people to go back to work, satisfy basic physical, valuable time sensitive opportunities for state governments, the mental and social needs, and eagerness to earn money as federal government, corporations and societal leaders to guide shown in descriptive public sentiment summary graph in Fig. local and regional communities, and the nation into a successful 1. However, there is also a significant sentiment to stay safe, new normal future. and many prefer the stay-at-home Lockdown measures to ensure lower spread of the Coronavirus [8]. Public sentiment I. INTRODUCTION has a significant impact on policy and politicians, and cannot be ignored [9]–[11]. Therefore, to a consequential measure, the reopening of America, and its states and regions will be HE anxiety, stress, financial strife, grief, and general influenced by perceived public sentiment. Tuncertainty of this time will undoubtedly lead to behavioral Hence, it is important to address the question: What is the health crises. - Coe and Enomoto, McKinsey on the dominant public sentiment in America concerning the reopen- COVID-19 crisis [1]. ing and in some form, going forward into a New Normal?. COVID-19 has become a paradigm shifting phenomenon ’New normal’ is a term being used to represent the potentially across domains and disciplines, affecting billions of people transformed socioeconomic systems [12], as result of COVID- 19 issues, amidst the likelihood of multiple future waves of the (Corresponding author: G.G.M.N. Ali). Coronavirus pandemic. There is a fear that the current Coro- J. Samuel and G.G.M.N. Ali are with the University of navirus wave will see a spike in COVID-19 infections with Charleston, WV, USA, e-mail: fjimsamuel,[email protected], [email protected]. reopening and associated loosening of Lockdown restrictions. M. M. Rahmain is with the University of North Carolina at Charlotte, The present study analyzed public sentiment using Tweets Charlotte, NC, USA and Khulna University of Engineering & Technology from the first nine days of the month of May, 2020, with a (KUET), Khulna, Bangladesh, e-mail:[email protected]. Y. Samuel is with the Northeastern University, Boston, MA, keyword “reopen” from users with country denoted as USA, to USA, e-mail:[email protected]. A. Pelaez is with the Hofstra gauge public sentiment along eight key dimensions of anger, University, NY, USA, e-mail:[email protected]. P. H.J. anticipation, disgust, fear, joy, sadness, surprise and trust, as Chong is with the Auckland University of Technology, NZ, email:[email protected]. M. Yakubov is with Theresumaniacs.com, visualized in Fig. 1. Twitter data and Tweets text corpus have NJ, USA, e-mail:[email protected]. been widely used in academic research and by practitioners NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.06.01.20119362; this version posted June 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . 2 Reopening Sentiments Summary use PPE (personal protective equipment) and strict public hygiene [30]. All of these would need to be implemented while protecting the most vulnerable sections of the population, using potential strategies such as the ’relax-at-home’ or ’safe- 1500 at-home’ mode. Moreover, the states would be expected to increase testing, tracing and tracking of COVID-19 cases, and 1000 ensure ample PPE supplies. Phase 3: It would be possible for people to go back to near-normal pre-Coronavirus lifestyles, Total Sentiment Score Total when proven vaccines and/or antibodies become commonly 500 available, and mass-adoption sets in. Early research shows that 90% of transmissions have taken place in closed environments, namely, home, workplace, restaurants, social gatherings and 0 trust anticipation fear sadness joy anger surprise disgust public transport, and such prevalence in critical social spaces Sentiment Categories contributed to increased fear sentiment [31], [32]. Technology driven social interaction and digital social spaces, on the Fig. 1. Reopening public sentiment summary contrary, can have a positive sentiment impact and reduce fear [33]. in multiple disciplines, including education, healthcare, expert and intelligent systems, and information systems [13]–[19]. Sentiment analysis with Tweets presents a rich research op- portunity, as hundreds of millions of Twitter users express their messages, ideas, opinions, feelings, understanding and beliefs through Twitter posts. Sentiment analysis has gained prominence in research with the development of advanced linguistic modeling frameworks, and can be performed using multiple well recognized methods, and tools such as R with readily available libraries and functions, and also through the use of custom textual analytics programming to identify dominant sentiment, behavior or characteristic trait [20]–[22]. Tweets analytics have also been used to study, and provide valuable insights on a diverse range of topics from public Fig. 2. Wordcloud summary of Tweets data. sentiment, politics and pandemics to stock markets [9], [23]– [27]. From a current sentiments analysis perspective, since a large There are strong circumstantial motivations, along with ratio of people need to start work, return to their businesses and urgent time-sensitivity, driving this research article. Firstly, jobs, and restart the economy, a quick reopening is perceived in the US alone, we have seen over 97,000 deaths and over as being strongly desirable. However, there is fear regarding 1.6 million COVID-19 cases, at the point of writing this a potential second outbreak of the COVID-19 pandemic, and manuscript, and the numbers continue to increase [28]. Sec- this presents a cognitive dilemma with implications for mental ondly, there have been significant economic losses and mass health and emotional conditions. Information and informa- psychological distress due to unprecedented job loss for tens tion formats have an impact on human sentiment, behavior of millions of people. These circumstantial
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