Local governments' use of social media during the COVID-19 pandemic: The case of Portugal
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ABSTRACT:
SUBMITTER: Padeiro M
PROVIDER: S-EPMC8517969 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Higher education has been shifted toward blended learning during the COVID-19 pandemic. An increase in social media usage intensity and reduced face-to-face interaction due to the COVID-19 pandemic urged instructional communication researchers to revisit the dynamics of learners' group development in terms of their socialization and academic performance during the COVID-19 crisis. This research aimed to determine the mediating role of social media sociability between face-to-face socialization and academic performance of higher education students in blended learning environments during the COVID-19 pandemic. It was also the aim of the study to determine the moderating effect of social media usage intensity on social media sociability. A cross-sectional survey was conducted with the students (n = 340) enrolled in science teacher education departments of universities in Pakistan. Partial least squares structural equation modeling (PLS-SEM) was used for multivariate analysis. Results revealed that face-to-face socialization gave an essential start to develop a learning group. However, when face-to-face socialization was reduced due to the COVID-19 pandemic, it was mediated by social media usage in blended learning environments to increase their socialization and academic performance during the crisis. The findings of the study are useful for higher education institutions to adopt social media strategies for students' socialization during the crisis.
| S-EPMC8583489 | biostudies-literature
Project description:Social media is the leading medium which is used for communication during the COVID-19 pandemic. The research conducted aims to fill the gap of literature related to social media use during the COVID-19 pandemic. This research aims at uncovering the influences of social media use in several dimensions during lockdown(s). The study aims to answer the research question of: Are the influences of social media use different from normal times? The online questionnaire has been completed by six hundred and sixty-eight users within the period of lockdown. The author prepared the questionnaire, which is composed of 22 positive statements in order to evaluate the effects of social media use during the COVID-19 pandemic. A 5 point Likert scale was used, where reliability and validity were calculated by the Cronbach's alpha value, which was 0.751. Findings highlight that users have more information about COVID-19, and they follow recent information via social media, which shows the shift towards digital medium. Findings also indicate that users are aware of fake news, and they follow official sources. Social media is powerful to affect decision-makers, and respondents' social media use did not create any panic or anxiety amongst them. This research indicates that respondents' social media use during COVID-19 is different from normal times as a common purpose triggers this, survival. Before the COVID-19 pandemic, most of social media shares were like a dream or a strong desire that may cause anxiety in others. During the pandemic, people are in lockdown and share similar feelings and follow similar behavioural patterns. As there is a common purpose and struggle via users, psychological well-being is not affected negatively.
| S-EPMC7834032 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic restricted everyday life during 2020-2021 for many people worldwide. It also affected alcohol consumption patterns and leisure activities, including the use of social media.ObjectiveThe aim of this study was to analyze whether social media use predicts increased risky drinking over time and during the COVID-19 pandemic restrictions in particular.MethodsThis 5-wave longitudinal survey study, based on a nationwide sample of workers, was conducted in Finland in 2019-2021. A total of 840 respondents (male: 473/840, 56.31%; age range 18-64 years; mean age 43.90, SD 11.14 years) participated in all 5 waves of the study. The outcome variable was risky drinking, measured using the 3-item Alcohol Use Disorders Identification Test (AUDIT-C). Multilevel linear hybrid modeling enabled the investigation of both within-person and between-person effects. Predictors included social media use and communication, involvement in social media identity bubbles, psychological distress, and remote working. Controls included sociodemographic factors and the Big Five personality traits.ResultsIncreased involvement in social media identity bubbles was associated with an increase in risky drinking behavior. Of all social media platforms examined, online dating app use was associated with riskier use of alcohol over time during the COVID-19 crisis. Daily social media communication with colleagues about nonwork topics was associated with risky drinking. Female gender, younger age, university education, nonindustrial occupational field, conscientiousness, agreeableness, and neuroticism were associated with lower levels of risky drinking.ConclusionsSocial media use during a pandemic carries some risks for alcohol consumption. Involvement in social media identity bubbles and online dating are risk factors for excessive drinking during the COVID-19 pandemic.
| S-EPMC8641700 | biostudies-literature
Project description:Municipalities in Lebanon represent local governments at the basic community level. The proximity of the municipality to the local community and its knowledge of available resources, can be crucial in easing the impact of any disaster. This study aimed to document the range of preparedness/reactivity of municipalities as COVID-19 swept through Lebanon. A qualitative case study was implemented to explore municipal response to control the epidemic, using in-depth semi-structured interviews with twenty-seven stakeholders from nine municipalities across all governorates in Lebanon. In each municipality, participants included mayors/deputy mayors, available members of municipal councils, prominent community leaders, health care professionals, and managers of local NGOs. The collected data were analyzed using the comparative thematic analysis. The socioecological model was adopted to illustrate the dynamic interplay between the barriers and facilitators at all ecological levels. The response to the pandemic differed significantly in volume and nature among different municipalities across regions, with rural areas clearly disadvantaged in terms of adequacy and completeness of response. Barriers consistently mentioned by most municipalities included economic collapse and poverty, shortage in resources, lack of support from the central government, stigma, lack of awareness, underreporting, flaws in the MOPH surveillance system, impeded accessibility to healthcare services, limited number and weak role of municipal police, increased mental illnesses, and political patronage, favoritism, and interference. On the other hand, increased donations, community engagement, social support and empathy, sufficient human resources, the effective role of healthcare systems, and good governance were identified as key facilitators. The socioecological model identified several multi-level facilitators and loopholes which can be addressed through a suggested strategic "roadmap" providing evidence-based interventions for future epidemics. It is crucial meanwhile that the central government strengthens the administrative and financial resources of municipalities in preparing and rapidly deploying the expected optimal response.
| S-EPMC8794115 | biostudies-literature
Project description:The unpredictability and unknowns surrounding the ongoing coronavirus disease (COVID-19) pandemic have led to an unprecedented consequence taking a heavy toll on the lives and economies of all countries. There have been efforts to predict COVID-19 case counts (CCC) using epidemiological data and numerical tokens online, which may allow early preventive measures to slow the spread of the disease. In this paper, we use state-of-the-art natural language processing (NLP) algorithms to numerically encode COVID-19 related tweets originated from eight cities in the United States and predict city-specific CCC up to eight days in the future. A city-embedding is proposed to obtain a time series representation of daily tweets posted from a city, which is then used to predict case counts using a custom long-short term memory (LSTM) model. The universal sentence encoder yields the best normalized root mean squared error (NRMSE) 0.090 (0.039), averaged across all cities in predicting CCC six days in the future. The R 2 scores in predicting CCC are more than 0.70 and often over 0.8, which suggests a strong correlation between the actual and our model predicted CCC values. Our analyses show that the NRMSE and R 2 scores are consistently robust across different cities and different numbers of time steps in time series data. Results show that the LSTM model can learn the mapping between the NLP-encoded tweet semantics and the case counts, which infers that social media text can be directly mined to identify the future course of the pandemic.
| S-EPMC9490453 | biostudies-literature
Project description:Abstract We study the role of social media in debates regarding two policy responses to COVID‐19 in Switzerland: face‐mask rules and contact‐tracing apps. We use a dictionary classifier to categorize 612'177 tweets by parties, politicians, and the public as well as 441'458 articles published in 76 newspapers between February and August 2020. We distinguish between “problem” (COVID‐19) and “solutions” (face masks and contact‐tracing apps) and, using a vector autoregression approach, we analyze the relationship between their salience on social and traditional media, as well as among different groups on social media. We find that overall attention to COVID‐19 was not driven by endogenous dynamics between the different actors. By contrast, the debate on face masks was led by the attentive public and by politicians, whereas parties and newspapers followed. The results illustrate how social media challenge the capacity of party and media elites to craft a consensus regarding the appropriateness of different measures as responses to a major crisis.
| S-EPMC8242806 | biostudies-literature
Project description: Not available
| S-EPMC7753419 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic is still undergoing complicated developments in Vietnam and around the world. There is a lot of information about the COVID-19 pandemic, especially on the internet where people can create and share information quickly. This can lead to an infodemic, which is a challenge every government might face in the fight against pandemics.ObjectiveThis study aims to understand public attention toward the pandemic (from December 2019 to November 2020) through 7 types of sources: Facebook, Instagram, YouTube, blogs, news sites, forums, and e-commerce sites.MethodsWe collected and analyzed nearly 38 million pieces of text data from the aforementioned sources via SocialHeat, a social listening (infoveillance) platform developed by YouNet Group. We described not only public attention volume trends, discussion sentiments, top sources, top posts that gained the most public attention, and hot keyword frequency but also hot keywords' co-occurrence as visualized by the VOSviewer software tool.ResultsIn this study, we reached four main conclusions. First, based on changing discussion trends regarding the COVID-19 subject, 7 periods were identified based on events that can be aggregated into two pandemic waves in Vietnam. Second, community pages on Facebook were the source of the most engagement from the public. However, the sources with the highest average interaction efficiency per article were government sources. Third, people's attitudes when discussing the pandemic have changed from negative to positive emotions. Fourth, the type of content that attracts the most interactions from people varies from time to time. Besides that, the issue-attention cycle theory occurred not only once but four times during the COVID-19 pandemic in Vietnam.ConclusionsOur study shows that online resources can help the government quickly identify public attention to public health messages during times of crisis. We also determined the hot spots that most interested the public and public attention communication patterns, which can help the government get practical information to make more effective policy reactions to help prevent the spread of the pandemic.
| S-EPMC8288653 | biostudies-literature
Project description:During the recent Covid-19 pandemic, additive Technology and Social Media were used to tackle the shortage of Personal Protective Equipment. A literature review and a social media listening software were employed to explore the number of the users referring to specific keywords related to 3D printing and PPE. Additionally, the QALY model was recruited to highlight the importance of the PPE usage. More than 7 billion users used the keyword covid or similar in the web while mainly Twitter and Facebook were used as a world platform for PPE designs distribution through individuals and more than 100 different 3D printable PPE designs were developed.
| S-EPMC7275995 | biostudies-literature
Project description:The restrictive measures adopted during the COVID-19 pandemic modified some previously consolidated drug use patterns. A focus on social networks allowed drug users to discuss, share opinions and provide advice during a worldwide emergency context. In order to explore COVID-19-related implications on drug trends/behaviour and on most popular psychotropic substances debated, the focus here was on the constantly updated, very popular, Reddit social platform's posts and comments. A quantitative and qualitative analysis of r/Drugs and related subreddits, using a social media listening netnographic approach, was carried out. The post/comments analysed covered the time-frame December 2019-May 2020. Between December 2019 and May 2020, the number of whole r/Drugs subreddit members increased from 619,563 to 676,581 members, respectively, thus increasing by 9.2% by the end of the data collection. Both the top-level r/Drugs subreddit and 92 related subreddits were quantitatively analysed, with posts/comments related to 12 drug categories. The drugs most frequently commented on included cannabinoids, psychedelics, opiates/opioids, alcohol, stimulants and prescribed medications. The qualitative analysis was carried out focussing on four subreddits, relating to some 1685 posts and 3263 comments. Four main themes of discussion (e.g., lockdown-associated immunity and drug intake issues; drug-related behaviour/after-quarantine plans' issues; lockdown-related psychopathological issues; and peer-to-peer advice at the time of COVID-19) and four categories of Redditors (e.g., those continuing the use of drugs despite the pandemic; the "couch epidemiologists"; the conspirationists/pseudo-science influencers; and the recovery-focused users) were tentatively identified here. A mixed-methods, social network-based analysis provided a range of valuable information on Redditors' drug use/behaviour during the first phase of the COVID-19 pandemic. Further studies should be carried out focusing on other social networks as well as later phases of the pandemic.
| S-EPMC8303488 | biostudies-literature