Defining Facets of Social Distancing during the COVID-19 Pandemic: Twitter Analysis

Kwon, Jiye; Grady, Connor B.; Feliciano, Josemari; Fodeh, Samah Jamal

doi:10.1101/2020.04.26.20080937

Cited by 8 publications

(7 citation statements)

References 19 publications

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“…Themes of previous studies that focus on exploration of, description of, correlation of, or predictive modeling with Twitter data during COVID-19 pandemic include sentiment analysis [17,[25][26][27][28], public attitude/interest measurement [21,[29][30][31], content analysis [15,[32][33][34][35][36], topic modeling [16,26,27,[37][38][39][40], analysis of misinformation, disinformation, or conspiracies [20,[41][42][43][44][45][46], outbreak detection or disease nowcasting/forecasting [18,19], and more [47][48][49][50][51][52]. Similarly, data from other social media channels (e.g., Weibo, Reddit, Facebook) or search engine statistics are utilized for parallel analyses related to COVID-19 pandemic as well [53][54][55][56][57][58][59][60][61]…”

Section: Going Beyond Correlationsmentioning

confidence: 99%

Causal Modeling of Twitter Activity during COVID-19

Gencoglu

Gruber

2020

Computation

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Understanding the characteristics of public attention and sentiment is an essential prerequisite for appropriate crisis management during adverse health events. This is even more crucial during a pandemic such as COVID-19, as primary responsibility of risk management is not centralized to a single institution, but distributed across society. While numerous studies utilize Twitter data in descriptive or predictive context during COVID-19 pandemic, causal modeling of public attention has not been investigated. In this study, we propose a causal inference approach to discover and quantify causal relationships between pandemic characteristics (e.g., number of infections and deaths) and Twitter activity as well as public sentiment. Our results show that the proposed method can successfully capture the epidemiological domain knowledge and identify variables that affect public attention and sentiment. We believe our work contributes to the field of infodemiology by distinguishing events that correlate with public attention from events that cause public attention.

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Section: Going Beyond Correlationsmentioning

confidence: 99%

Causal Modeling of Twitter Activity during COVID-19

Gencoglu

Gruber

2020

Computation

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“…Researchers across the world are promptly trying to address this issue by screening the psychological impact of social distancing and quarantining ( Brooks et al, 2020 ; Orrù et al, 2020 ; Poli et al, 2020 ). Results from early studies using social media like Twitter and Weibo data have found that posts related to negative emotions and sensitivity to social risks have greatly increased during lockdown ( Kwon et al, 2020 ; Li et al, 2020 ). Consistent with these findings, another study on the psychological impact of COVID-19 among Italians during the first week of lockdown has found that 40% of participants reported high psychological distress and about 30% showed clinically significant post-traumatic symptoms ( Marazziti et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Mindfulness, Age and Gender as Protective Factors Against Psychological Distress During COVID-19 Pandemic

et al. 2020

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Objective: Mindfulness disposition is associated with various psychological factors and prevents emotional distress in chronic diseases. In the present study, we analyzed the key role of mindfulness dispositions in protecting the individual against psychological distress consequent to COVID-19 social distancing and quarantining. Methods: An online survey was launched on March 13, 2020, with 6,412 responses by April 6, 2020. Socio-demographic information, exposure to the pandemic, and quarantining were assessed together with psychological distress and mindfulness disposition. Multivariate linear regression analysis was performed to study the influence of predictive factors on psychological distress and quality of life in Italian responders during the early days of lockdown. Pearson correlations were calculated to study the relationship between mindfulness and psychiatric symptoms. Results: Multivariate linear regression run on socio-demographics, COVID-19-related variables, and mindfulness disposition as moderators of overall psychological distress showed that mindfulness was the best predictor of psychological distress (β = −0.504; p < 0.0001). High negative correlations were found between mindfulness disposition and the overall Global Severity Index (r = −0.637; p < 0.0001), while moderate to high associations were found between mindfulness and all SCL-90 sub-scales. Discussion: Findings showed that high dispositional mindfulness enhances wellbeing and helps in dealing with stressful situations such as the COVID-19 pandemic. Mindfulness-based mental training could represent an effective intervention to stem post-traumatic psychopathological beginnings and prevent the onset of chronic mental disorders.

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“…Social distancing has been one of the primary mitigation strategies used across the World to control the spread of COVID-19. Twitter analysis (an American based microblogging and social networking service) has shown that posts related to implementation and negative emotions around social distancing largely dominated their media platform, in combination with topics of social disruption and adaptation 1 . Analysis of Weibo posts (a Chinese based microblogging website) suggested that negative emotions (for example anxiety, depression and indignation) and sensitivity to social risks increased, while the scores of positive emotions (for example Oxford happiness) and life satisfaction decreased.…”

Section: Introductionmentioning

confidence: 99%

Psychological defence mechanisms during the COVID-19 pandemic: A case series

Walker

McCabe

2021

The European Journal of Psychiatry

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Background and objectives COVID-19 has had a negative effect on mental health across the world's population. Healthcare workers in particular have experienced increased levels of psychological distress, depression and anxiety. Any perceived stress to an individual can provoke psychological defence mechanisms. Using psychoanalytic theory, a defence mechanism is described as an unconscious psychological strategy, with or without resulting behaviour, which aims to reduce or eliminate anxiety arising from unacceptable or potentially harmful stimuli. This paper aims to describe a range of psychological defence mechanisms encountered within colleagues in relation to the COVID-19 pandemic. Methods Using the methodology of a case series, specific defence mechanisms are explored with reference to further literature in the field. Results The author has encountered varying psychological defence mechanisms, both within himself and in other members of the multidisciplinary team. These have been illustrated in the attached clinical vignettes, relating to the specific psychological coping mechanisms of; denial, hypochondriasis, altruism, sublimation and humour. Conclusion We encourage acknowledgement of psychological defence mechanisms and their implications on day to day practice. Whilst defence mechanisms can have a number of negative consequences as described in this article, they also have an important role, particularly in the case of mature defence mechanisms, as protective factors against psychological distress and symptom formation. Deeper understanding of the gold-standard hierarchical organization of defence mechanisms could help increase utilisation of specific therapeutic interventions for enhancing changes from immature to mature defensive responses to stressful experiences as the COVID-19 pandemic progresses.

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Defining Facets of Social Distancing during the COVID-19 Pandemic: Twitter Analysis

Cited by 8 publications

References 19 publications

Causal Modeling of Twitter Activity during COVID-19

Causal Modeling of Twitter Activity during COVID-19

Mindfulness, Age and Gender as Protective Factors Against Psychological Distress During COVID-19 Pandemic

Psychological defence mechanisms during the COVID-19 pandemic: A case series

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