Tweet you right back: Follower anxiety predicts leader anxiety in social media interactions during the SARS-CoV-2 pandemic.

Recent research has shown that organizational leaders' tweets can influence employee anxiety. In this study, we turn the table and examine whether the same can be said about followers' tweets. Based on emotional contagion and a dataset of 108 leaders and 178 followers across 50 organizations, we infer and track state- and trait-anxiety scores of participants over 316 days, including pre- and post the onset of the SARS-CoV-2 pandemic and crisis.

Is it too late now to say we're sorry? Examining anxiety contagion and crisis communication strategies using machine learning.

In this paper, we explore the role of perceived emotions and crisis communication strategies via organizational computer-mediated communication in predicting public anxiety, the default crisis emotion. We use a machine-learning approach to detect and predict anxiety scores in organizational crisis announcements on social media and the public's responses to these posts. We also control for emotional and language tones in organizational crisis responses using a separate machine learning algorithm.

Generating actionable insights from free-text care experience survey data using qualitative and computational text analysis: A study protocol.

The National Care Experience Programme (NCEP) conducts national surveys that ask people about their experiences of care in order to improve the quality of health and social care services in Ireland. Each survey contains open-ended questions, which allow respondents to comment on their experiences. While these comments provide important and valuable information about what matters most to service users, there is to date no unified approach to the analysis and integration of this detailed feedback.

COVID-19 pandemic disruptions to working lives: A multilevel examination of impacts across career stages.

Since early 2020 the COVID-19 pandemic disrupted societies worldwide. As we moved from expecting the closure of society to be a short-term one to experiencing it as a longer-term phenomenon, we lacked understanding about how the pandemic has affected the working lives and wellbeing of employees in different life and career stages. Drawing from lifespan development approaches and Job Demands-Resources (JD-R), we considered the effect this profound disruption had on stress, burnout, and job satisfaction across career stages over time.

Don't you tweet me badly: Anxiety contagion between leaders and followers in computer-mediated communication during COVID-19.

Do organizational leaders' tweets influence their employees' anxiety? And if so, have employees become more susceptible to their leader's social media communications during the COVID-19 pandemic? Based on emotional contagion and using machine learning algorithms to track anxiety and personality traits of 197 leaders and 958 followers across 79 organizations over 316 days, we find that during the pandemic leaders' tweets do influence follower state anxiety. In addition, followers of trait anxious leaders seem somewhat protected by sudden spikes in leader state anxiety, while followers of less trait anxious leaders are most affected by increased leader state anxiety. Multi-day lagged regressions showcase that this effect is stronger post-onset of the COVID-19 pandemic compared to the pre-pandemic crisis context.

All about that trait: Examining extraversion and state anxiety during the SARS-CoV-2 pandemic using a machine learning approach.

We examine the longitudinal relation between extraversion and state anxiety in a large cohort of New York City (NYC) residents using a linguistic analytical machine learning approach. Anxiety, both state and trait, and Big Five personality traits were predicted using micro-blog data on the Twitter platform. In total, we examined 1336 individuals and a total of 200,289 observations across 246 days.