Toward dialogue through a holistic measuring framework – the impact of social media on risk communication in the COVID-19

Information under lockdown: A content analysis of government communication strategies on Facebook during the COVID-19 outbreak

The aim of this study is to investigate how central government agencies used social media to communicate and disseminate information to the public during the Coronavirus outbreak. In addition, this study seeks to examine the characteristics of the messages, content, and engagement rates of the information which has been published by the four central government bodies responsible for the management of the emerging crisis in Israel. This article is based on content analysis to examine the work of four main government ministries on Facebook (Ministry of Health, Ministry of Defense, Ministry of Education and Ministry of Finance) throughout the first six months of the crisis from February to July 2020. Findings indicate that The Ministry of Health's posts yielded the highest engagement rates compared to the rest of the ministries. Also, we categorized the posts into four main categories: Policy, Advocacy & COVID-19 additional information, Restrictions, Guidelines & Recommendations. In terms of Sentiment analysis, posts containing restrictions have created the highest emotional reactions (positive and negative). Research findings can be deduced regarding modes of distribution in terms of messages, publication dates, and types of content to improve users' responses in terms of audience engagement and sentiment.

Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism

With the increasing use of social media, online self-organized relief has become a crucial aspect of crisis management during public health emergencies, leading to the emergence of online self-organizations. This study employed the BERT model to classify the replies of Weibo users and used K-means clustering to summarize the patterns of self-organized groups and communities. We then combined the findings from pattern discovery and documents from online relief networks to analyze the core components and mechanisms of online self-organizations. Our findings indicate the following: (1) The composition of online self-organized groups follows Pareto's law. (2) Online self-organized communities are mainly composed of sparse and small groups with loose connections, and bot accounts can automatically identify those in need and provide them with helpful information and resources. (3) The core components of the mechanism of online self-organized rescue groups include the initial gathering of groups, the formation of key groups, the generation of collective action, and the establishment of organizational norms. This study suggests that social media can establish an authentication mechanism for online self-organizations, and that authorities should encourage online interactive live streams about public health issues. However, it is important to note that self-organizations are not a panacea for all issues during public health emergencies.

Exploring the pathway from seeking to sharing social support in e-learning: an investigation based on the norm of reciprocity and expectation confirmation theory

E-learning is increasingly evidenced as a conduit for social support exchange among students and protects them against mental health issues, however, the cognitive process of how social support is exchanged remains unclear. This study uses a cognitive theory approach to achieve a more nuanced explanation of students sharing or giving social support in e-learning. Specifically, we adopted the Norm of Reciprocity and Expectation Confirmation Theory to reveal the interconnection between students' perceived social support and giving social support in learning. The model is empirically validated based on survey data of 512 respondents from college students across China regarding their e-learning experience during the first wave of Covid-19. Our findings suggest that the relationship between perceived social support and giving social support is significant and positive, and this relationship is partially mediated by confirmation of social support. These findings imply that e-learning can foster a self-reliant environment for social support exchange among college students. Under such an environment, students' cognitive process in their seeking and sharing social support is majorly following the norm of reciprocity and secondary expectation confirmation theory.

Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic

BACKGROUND

Emotional support in social media can act as a buffer against the negative impact of affective disorders. However, empirical evidence relating to emotional support in social media and how it influences the wider public remains scanty. The objective of this study is therefore to conduct a prototype investigation into the translation mechanism of emotional support in social media, providing empirical evidence for practitioners to use to tackle mental health issues for the wider public.

METHODS

A regression model is proposed to examine the relationship between perceived and received emotional support. Received emotional support is set as the dependent variable and measured using public activity. Perceived emotional support is derived using Natural Language Processing (NLP)-based content analysis. The model is then analyzed using a panel date with a total number of 61,297 posts from 17 Weibo accounts in 17 provincial administrative units in China.

RESULTS

The relationship between perceived and received emotional support is not linear but complex, suggesting that translation of emotional support is not automatic. Further, our empirical evidence suggests that the translation of emotional support in social media is affected by frequency and pandemic stage.

LIMITATIONS

The study does not examine the direct relationship between perceived and received emotional support, instead adopting public activity as a proxy for the latter construct. In addition, the relationship between perceived and received emotional support is more complex than linear, requiring further model and theory development.