Crisis Communications on Social Media: Insights from Canadian Officials Twitter Presence during COVID-19 Pandemic

COVID-19 pandemic is a unique case in crisis management given its length, scale, several different response systems, and public officials' extensive social media use for crisis communication. Leveraging text mining techniques, we examine Canadian officials' presence on Twitter during the pandemic by focusing on their COVID-19-related content. We identified eight themes of discussion that unveil 37 relevant sub-themes. Concentrating on the COVID-19-addressing themes, we reveal that educating citizens on the safety information and keeping them informed with the latest crisis information was the Canadian officials' primary focus during the pandemic. To fight COVID-19, Canadian officials used four policies, and to implement those, they promoted eight measures and practices. According to the volume of generated content, the evolution of COVID-19-addressing themes over time, and their coexistence; Test and trace was the most advocated policy by emphasizing screening the symptoms. To stop the spread of COVID-19, Canadian officials promoted wearing Mask, Social distancing, Hand washing, and Stay home, where Mask and Social distancing were the most frequent practices. Our study contributes to crisis communication and management by depicting how Canadian officials leveraged social media during such a big-scale crisis

CRISIS COMMUNICATION DURING HEALTH CRISES: THE CASE OF CANADIAN OFFICIALS’ SOCIAL MEDIA PRESENCE DURING THE COVID-19 PANDEMIC

To effectively manage a health crisis, citizens need to have shared Situational Awareness (SA) of the crisis. This study proposes that the public draws upon shared mental models of the crisis to achieve shared SA. Declarative, procedural, and strategic knowledge bases comprise the essential aspects of shared mental models of mission-critical situations like the COVID-19 pandemic. Therefore, public officials must provide a constant flow of crisis declarative, procedural, and strategic knowledge on social media. This study investigates Canadian officials’ presence on Twitter during the COVID-19 pandemic. Analyzing a dataset of 213,089 Canadian officials’ tweets shows that their presence was either for health crisis management (73.26%) or crisis-related topics (46.66%). Declarative (72.03%), procedural (38.1%), and strategic knowledge (30.18%) comprised 96% of the health crisis management tweets. This study informs research and practice by analyzing the essential role of knowledge types in creating a shared SA in managing health crises

Legacy and social media respectively influence risk perceptions and protective behaviors during emerging health threats: A multi-wave analysis of communications on Zika virus cases.

ObjectiveBoth legacy media, such as television and newspapers, and online social media are potentially important but incompletely understood sources of information in the face of emerging public health risks. This research aimed to understand media effects on risk perceptions and behaviors concerning the Zika virus in the United States.MethodsWe analyzed a multi-wave nationally representative survey (N = 29,062) and the volume of communications in social and legacy media (i.e., legacy media data from news sources and databases, N = 2,660 and social media data from Twitter, N = 1,605,752) in the United States between April and October 2016, dates coinciding with the early cases of local transmission of Zika in the United States (i.e., 25 weeks). The present study conducted econometric analyses (i.e., Granger causality tests) to assess the associations of legacy and social media coverage with risk perceptions and protective behaviors in the total sample and specific groups separated by pregnancy status/intent, geographic region, income, education level, age, and ethnicity.ResultsThe results from the overall sample suggested that changes in the volume of information in legacy and social media (i.e., Twitter) were followed by different changes in community risk perceptions and protective behaviors. Specifically, social media coverage correlated with the level of risk perceptions, whereas the legacy media coverage correlated with the level of protective behaviors. Analyses across different subpopulations, including those of different pregnancy status/intent, geographic Zika risk, income, education level, age, and ethnicity, replicated the social media associations with risk perceptions in most cases. However, legacy media and protective behaviors were linked only in some vulnerable subpopulations (e.g., the less-educated populations).ConclusionUnderstanding how media coverage relates to Zika risk perceptions and protective behaviors will help to facilitate effective risk communications by healthcare professionals and providers, particularly when a health risk emerges

Statistical Models for Aspect-Level Sentiment Analysis

Sentiment analysis and opinion mining is the field of computational study of people’sopinion expressed in written language or text. Sentiment analysis brings together variousresearch areas such as natural language processing, data mining and text mining,and is fast becoming of major importance to organizations as they integrate online commerceinto their operations.The input of the problem is a collection of written reviews about an object. The object could be a product or service and the goal is to discover people’s opinions expressed in those written reviews. The input reviews are in the form of free text and do not have any structure (people can write whatever they like however they want). Dealing with unstructured data is a challenging problem.Sentiment analysis can be done in different levels, and the focus of this dissertationin on aspect-level sentiment analysis. In aspect-level sentiment analysis there are twotasks that need to be addressed. The first task is aspect identification which is the processof discovering those attributes of the object that people are commenting on. Theseattributes of the object are called aspects. The second task is sentiment identificationwhich is the process of discovering people’s opinions expressed about each one of theaspects. Aforementioned tasks can be solved in 2 separate steps or can be solved simultaneously.Early work on aspect-level sentiment analysis would solve it in 2 steps and recent techniques based on topic models address these 2 tasks simultaneously. In this thesis an automatic framework for discovering the aspects and their corresponding sentiments is proposed. This framework first identifies the aspects and then in the next step classifies each sentence containing one of the discovered aspects into either positive, neutral or negative sentiment classes. In the subsequent chapter this framework is used to give structure to input data which does not have any structure. Also a Bayesian model is proposed for overall satisfaction that accurately predicts the overall customer satisfaction and also the significance of each discovered aspect from the contributors perspectives. Hierarchical Bayesian frameworks are powerful tools that have recently attracted a lot of attention in the machine learning community. In this dissertation a new model based on hierarchical Bayesian models is proposed to simultaneously discover aspects and sentiments. This framework is based on probabilistic topic modeling techniques

To Be or Not to Be Dynamic: Exploring Antecedents and Contextual Factors of Dynamic Capabilities

Firms are known to struggle to find the best recipe for achieving different forms of innovation, digital transformation, and superior performance based on their bundle of resources and strategies in the presence of various environmental factors that can pose new opportunities and threats. In this vein, although the dynamic capabilities (DC) framework can explain how firms address competitive advantage, especially in uncertain environments, it is still not clear how these capabilities are built. To fill this gap, we aim at investigating the antecedents of organizational dynamic capabilities and eventually presenting a big-picture framework that includes almost every internal and external factor that might play a role in the process of building organizational dynamic capabilities. By exploring the adoption of the affordance lens and considering the role of organizational strategic alignment, we lay the foundation for future research into the mechanisms and micro-foundations of dynamic capabilities

The Effects of Nonpharmaceutical Interventions on COVID-19 Cases, Hospitalizations, and Mortality: A Systematic Literature Review and Meta-analysis

Introduction: This review aimed to assess the effects of various nonpharmaceutical interventions on cases, hospitalizations, and mortality during the first wave of the COVID-19 pandemic. Methods: To empirically investigate the impacts of different nonpharmaceutical interventions on COVID-19–related health outcomes, a systematic literature review was conducted. The effects of 10 nonpharmaceutical interventions on cases, hospitalizations, and mortality across 3 periodic lags (2, 3, and ≥4 weeks after implementation) were studied. Articles measuring the impact of nonpharmaceutical interventions were sourced from 3 databases by May 10, 2022, and risk of bias was assessed using the Newcastle-Ottawa scale. Results: Across the 44 papers, the authors found that policy stringency corresponded to decreased per capita mortality across all lags (–0.13, –0.24, and –0.24 per 100,000, respectively). Masks were associated with mitigative effects on both cases (–2.76 per 100,000) and deaths (–0.19 per 100,000), whereas restaurant closures and travel restrictions corresponded to decreased mortality. Shelter-in-place orders suggested later impacts (after 2 weeks) on cases (–2.9 per 100,000). Although limited gatherings and school and business closures corresponded to reduced per capita mortality in 2 or 3 weeks, or both, their impacts diminished after 4 weeks. The 3 nonpharmaceutical interventions studied in hospitalizations showed negative estimates. Discussion: When assessing the impact of nonpharmaceutical interventions, considering the duration of effectiveness after implementation has paramount significance. Although some nonpharmaceutical interventions may reduce the COVID-19 impact, others can disrupt the mitigative progression of containing the virus after 3 weeks. Policymakers should be aware of both the scale of their effectiveness and duration of impact when adopting these measures for future COVID-19 waves

Attitudes towards vaccines and intention to vaccinate against COVID-19: a cross-sectional analysis - implications for public health communications in Australia

Objective To examine SARS-CoV-2 vaccine confidence, attitudes and intentions in Australian adults as part of the iCARE Study. Design and setting Cross-sectional online survey conducted when free COVID-19 vaccinations first became available in Australia in February 2021. Participants Total of 1166 Australians from general population aged 18-90 years (mean 52, SD of 19). Main outcome measures Primary outcome: responses to question € If a vaccine for COVID-19 were available today, what is the likelihood that you would get vaccinated?'. Secondary outcome: analyses of putative drivers of uptake, including vaccine confidence, socioeconomic status and sources of trust, derived from multiple survey questions. Results Seventy-eight per cent reported being likely to receive a SARS-CoV-2 vaccine. Higher SARS-CoV-2 vaccine intentions were associated with: increasing age (OR: 2.01 (95% CI 1.77 to 2.77)), being male (1.37 (95% CI 1.08 to 1.72)), residing in least disadvantaged area quintile (2.27 (95% CI 1.53 to 3.37)) and a self-perceived high risk of getting COVID-19 (1.52 (95% CI 1.08 to 2.14)). However, 72% did not believe they were at a high risk of getting COVID-19. Findings regarding vaccines in general were similar except there were no sex differences. For both the SARS-CoV-2 vaccine and vaccines in general, there were no differences in intentions to vaccinate as a function of education level, perceived income level and rurality. Knowing that the vaccine is safe and effective and that getting vaccinated will protect others, trusting the company that made it and vaccination recommended by a doctor were reported to influence a large proportion of the study cohort to uptake the SARS-CoV-2 vaccine. Seventy-eight per cent reported the intent to continue engaging in virus-protecting behaviours (mask wearing, social distancing, etc) postvaccine. Conclusions Most Australians are likely to receive a SARS-CoV-2 vaccine. Key influencing factors identified (eg, knowing vaccine is safe and effective, and doctor's recommendation to get vaccinated) can inform public health messaging to enhance vaccination rates