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1.
Online Information Review ; : 18, 2022.
Article in English | Web of Science | ID: covidwho-1816422

ABSTRACT

Purpose - The study aimed to examine how different communities concerned with dementia engage and interact on Twitter. Design/methodology/approach - A dataset was sampled from 8,400 user profile descriptions, which was labelled into five categories and subjected to multiple machine learning (ML) classification experiments based on text features to classify user categories. Social network analysis (SNA) was used to identify influential communities via graph-based metrics on user categories. The relationship between bot score and network metrics in these groups was also explored. Findings - Classification accuracy values were achieved at 82% using support vector machine (SVM). The SNA revealed influential behaviour on both the category and node levels. About 2.19% suspected social bots contributed to the coronavirus disease 2019 (COVID-19) dementia discussions in different communities. Originality/value - The study is a unique attempt to apply SNA to examine the most influential groups of Twitter users in the dementia community. The findings also highlight the capability of ML methods for efficient multi-category classification in a crisis, considering the fast-paced generation of data.

2.
Naunyn-Schmiedeberg's Archives of Pharmacology ; 395(SUPPL 1):S21-S22, 2022.
Article in English | EMBASE | ID: covidwho-1813652

ABSTRACT

Question: Prominent opinions, media coverage and guidelines may have an impact on drug usage and subsequent harmful adverse events (AE). The impact of the public attention to drugs by media coverage has been estimated for both prescriptions and purchases. Consequences on drug therapy safety are largely unknown. Methods: We analysed U.S. American pharmacovigilance data using OpenVigil 2 to identify drugs used against coronavirus infections (coded as preferred terms of the Standardized MedDRA Query 'COVID-19 (SMQ)') and their other indications and depicted them weekly aggregated. EMA and FDA approvals and withdrawals, news headlines concerning these drugs and the publication date of scientific papers were annotated in order to explain the temporal change of spontaneous reporting. Results: AE were most commonly reported for the drugs (in descending order): hydroxychloroquine (n=1873, 15.7%), remdesivir (14.2%), bamlanivimab (9.2%), azithromycin (8.2%), tocilizumab (6.2%), ritonavir/lopinavir (4.8%), dexamethasone (4%). Recently emerging trending drugs like ivermectin are yet a minority (0.38%). For all off-label cases, the reported adverse events were mostly not a consequence of the disease but the inappropriate or excess use of the drug. The extracted reports showed, that not only approvals/withdrawals, on- and off-label recommendations, clinical guidelines based on expert opinions and scientific articles, but also prominent lay opinions and rumors in social networks contribute to drug usage and thus subsequent adverse events. E.g., for hydroxychloroquine, the coverage of a prominent opinion in lay media and a subsequent scientific article nine weeks later had the strongest impact on its off-label use against coronavirus infections (fig. 1). Commonly reported adverse events, ranked by their proportional reporting ratio (PRR) were: cardiac arrhythmias like prolonged QT time 27.6 and ventricular extrasystoles 5.8, type IV allergies like eosinophilia 23.2, AGEP 18.4 or DRESS 25.9, electrolyte disturbances like hypernatraemia 20.3. The mortality for the event prolonged QT time associated with hydroxychloroquine was 20.5% when used against COVID-19, as compared to only 11.1% for all other indications (Odds ratio 2.1, p<0.01). Conclusion: Media coverage has an influence on drug usage and subsequent adverse events. A high mortality suggests a patient relevant impact. Lay opinions and social media may account for a loss of drug therapy safety.

3.
Sustainability ; 14(8):4748, 2022.
Article in English | ProQuest Central | ID: covidwho-1810164

ABSTRACT

Several biosafety gaps in agri-food sectors have become evident in recent years. Many of them are related to the global livestock systems and the organizational models involved in their management and organization. For example, producing pigs requires a global system of massive confinement and specific technological innovations related to animal production and health that involve broad technical and scientific structures, which are required to generate specific knowledge for successful management. This suggests the need for an underlying socially agglomerated technological ecosystem relevant for these issues. So, we propose the analysis of a specialized scientific social structure in terms of the knowledge and technologies required for pig production and health. The objective of this work is to characterize structural patterns in the research of the swine health sector worldwide. We use a mixed methodological approach, based on a social network approach, and obtained scientific information from 4868 specialized research works on health and pig production generated between 2010 to 2018, from 47 countries. It was possible to analyze swine research dynamics, such as convergence and influence, at country and regional levels, and identify differentiated behaviors and high centralization in scientific communities that have a worldwide impact in terms of achievements but also result in significant omissions.

4.
Social Sciences ; 11(4):158, 2022.
Article in English | ProQuest Central | ID: covidwho-1810124

ABSTRACT

Where do people meet? And how does their region’s wealth effect where they meet? Investigating these patterns across the United States, we explore community organization and association venues based on data provided from Meetup.com. Examining how individuals associate for business, social, and cultural reasons, we discover that a region’s median income significantly affects the type of venue for the meeting. However, certain types of associations centered on a select group of topics mitigate that effect. We discover that in the United States, personal social capital that is built and maintained “in person” is deeply embedded in commercial activities. As a result, access to various types of community is often limited to economically advantaged geographies.

5.
Land ; 11(4):476, 2022.
Article in English | ProQuest Central | ID: covidwho-1810000

ABSTRACT

As a vital component of public space, public open space (POS) is considered crucial for community regeneration. However, most evaluation studies have focused on the geographical attributes of POS, and those assessing renewal holistically in terms of residents’ everyday lives are limited. Drawing on the Ruijin community in Shanghai, this study compared networks of public space layout and residents’ daily behaviours as a function of their structure and individual nodes using the Social Network Analysis method to explore the characteristics and evaluate the effectiveness of renewal. The results showed: (1) the current renewal while increasing recreational opportunities and improving spatial appearance has had a limited effect at the social level. (2) There are differentiations between the two networks. POS plays different roles in the behavioural network, including comprehensive, intermediary, and directional nodes. (3) The core POSs have frequent interactions and strong links with specific types of public facilities than the periphery. Therefore, we suggested that POS renewal should be conducted according to the rule of “core preceding periphery, comprehensive high-efficiency preceding single low-efficiency” and explain the necessity of public participation in the process. These findings shed light on the potential mechanism of the impact of POS on everyday life and rethink the construction management and governance of urban community regeneration in the era of sustainability.

6.
ISPRS International Journal of Geo-Information ; 11(4):267, 2022.
Article in English | ProQuest Central | ID: covidwho-1809936

ABSTRACT

The cross-impact of environmental pollution among cities has been reported in more research works recently. To implement the coordinated control of environmental pollution, it is necessary to explore the structural characteristics and influencing factors of the PM2.5 spatial correlation network from the perspective of the metropolitan area. This paper utilized the gravity model to construct the PM2.5 spatial correlation network of ten metropolitan areas in China from 2019 to 2020. After analyzing the overall characteristics and node characteristics of each spatial correlation network based on the social network analysis (SNA) method, the quadratic assignment procedure (QAP) regression analysis method was used to explore the influence mechanism of each driving factor. Patent granted differences, as a new indicator, were also considered during the above. The results showed that: (1) In the overall network characteristics, the network density of Chengdu and the other three metropolitan areas displayed a downward trend in two years, and the network density of Wuhan and Chengdu was the lowest. The network density and network grade of Hangzhou and the other four metropolitan areas were high and stable, and the network structure of each metropolitan area was unstable. (2) From the perspective of the node characteristics, the PM2.5 spatial correlation network all performed trends of centralization and marginalization. Beijing-Tianjin-Hebei and South Central Liaoning were “multi-core” metropolitan areas, and the other eight were “single-core” metropolitan areas. (3) The analysis results of QAP regression illustrated that the top three influencing factors of the six metropolitan areas were geographical locational relationship, the secondary industrial proportion differences, respectively, and patent granted differences, and the other metropolitan areas had no dominant influencing factors.

7.
International Journal of Medical Engineering and Informatics ; 14(3):282-294, 2022.
Article in English | ProQuest Central | ID: covidwho-1808592

ABSTRACT

The propagation of the new pandemic COVID-19 is more likely linked to human social relations and activities. A social network can be used to describe these human relationships and activities. Understanding the dynamic properties of disease dissemination through diverse social networks is critical for effective and efficient infection prevention and control. With the frequent emergence and spread of infectious diseases and their impact on large areas of the population, there is growing interest in modelling these complex epidemic behaviour. Such an approach could provide a stronger decision-making method to tackle and control disease. In this paper, a transmission network is developed using the South Korean data, and the study of the network is carried out using graph energy centrality. This measure of centrality allows us to recognise the primary cause of the spread of the virus within the established network by ranking the nodes of the network based on graph energy. The identified primary cause can then be isolated, which can prevent further spread of infection. We have also considered the Novel_Corona_Virus_2019_Dataset from Johns Hopkins University to analyse epidemiological data around the world.

8.
Sage Open ; 12(2):16, 2022.
Article in English | Web of Science | ID: covidwho-1799138

ABSTRACT

One of the effective ways of preventing the spread of the COVID-19 outbreak is dependent on non-pharmaceutical interventions due to the absence of a vaccine against the virus. This study aims to assess organizational emergency responses to COVID-19 using a social network analysis (SNA) method via Gephi. The data were obtained from a weekly Indonesian magazine, TEMPO, which reported on the Indonesian government's response to COVID-19 from early March to early April 2020. One hundred and fifty actors represent the nodes and 180 connections denoted as edges are explored and analyzed using the SNA tool. The study found that the emergency response to the pandemic consisted of less solid, non-traditional structural interactions, and that the head of the task force played a lesser role in the response to this outbreak. The content analysis revealed that the team members' issues of concern included coordination, hoaxes and fake issues, instruction/consultation, social distancing, and the lack of testing equipment. The results of the study are expected to contribute to the literature on research on emergency responses to pandemics. The findings also contribute to the development of the design of organizational emergency policies in the contexts of large-scale pandemics.

9.
Int J Environ Health Res ; : 1-13, 2022.
Article in English | PubMed | ID: covidwho-1795528

ABSTRACT

Exposure setting is crucial in the formation and propagation of SARS-CoV-2 transmission clusters. In this cohort study, transmission networks of 2 waves were differentiated by exposure setting using territory-wide surveillance data with clinical and laboratory records in Hong Kong. Characteristically, the first wave had resulted from imported cases followed by local transmissions, while the second wave was constituted primarily by local infections. With a 4-fold higher caseload, the second wave featured predominance of epidemiologically linked, local, older and asymptomatic patients with higher viral loads and shorter inpatient days. The 1028 transmission clusters formed 155 cascades composing at least two clusters. Daily and social activities were exposure settings that bridged clusters while residences usually terminated transmission cascades. Regulatory restrictions on social activities extinguished cluster formation in bars, but shifted to private parties in the second wave. The results confirmed that strategic interventions targeting exposure settings could achieve effective epidemic control.

10.
J. Asian Financ. Econ. Bus. ; 9(3):65-76, 2022.
Article in English | Web of Science | ID: covidwho-1791697

ABSTRACT

This study will examine the relationship between social support from the work and family domains, referred to as multiple social network ties (MSNT), and employees' job and family-related performance outcomes during the COVID-19 crisis. The study also demonstrates the importance of employees' work-family balance (WFB) in moderating the association between MSNT and job and family-related performance. A two-wave design was used to collect data from 320 managerial level personnel in Pakistan's textile sector. The path analysis technique of structural equation modelling (SEM) was used to analyze the responses. In times of crisis, social support mechanisms could potentially replace organizational support mechanisms for employees dealing with work and family obligations, according to the study. The findings of this study show that work-family balance is a significant partial mediator between MSNT and employees' job and familyrelated outcomes during the COVID-19 pandemic, according to a best-fit model. This research supports the pragmatic view of MSNT's action mechanism in generating jobs for employees and family-related results, especially in uncertain situations. According to the findings, employees who have a positive work-life balance are happier and more productive in both work and personal life. It has major implications for human resource management (HRM) research and practice.

11.
Empiria ; - (53):121-145, 2022.
Article in Spanish | Web of Science | ID: covidwho-1790573

ABSTRACT

Connective parties were originated as the response to the citizens inclinations towards the shared decision making and horizontality. To accomplish that, they delegate part of their organization to online tools on the net. In this research we study if those connective parties actually represent an innovation in terms of political representation. Thus, we observe - on an external level - the communicative manners of the connective party Podemos in comparison with four parties which hold the higher representation in the Spanish congress during the state of alarm in Spain due to the COVID-19 pandemic. To this end, we measure the interactions and responses rate of the deputies in Twitter to the interpellations of the users and we determine if these are higher according to the message impact on the net or when it comes to users with greater influence and communicative power. Our results show that the external communication patterns of Podemos correspond to a vertical criterion in terms of communication which is typical of traditional parties.

12.
11th International Conference on Computer Engineering and Knowledge, ICCKE 2021 ; : 30-33, 2021.
Article in English | Scopus | ID: covidwho-1788698

ABSTRACT

One of the most important incidents in the world in 2020 is the outbreak of the Coronavirus. Users on social networks publish a large number of comments about this event. These comments contain important hidden information of public' opinion regarding this pandemic. In this research, a large number of Coronavirus- related tweets are considered and analyzed using natural language processing and information retrieval science. Initially, the location of the tweets is determined using a dictionary prepared through the Geo-Names geographic database, which contains detailed and complete information of places such as city names, streets, and postal codes. Then, using a large dictionary prepared from the terms of economics, related tweets are extracted and sentiments corresponded to tweets are analyzed with the help of the RoBERTa language-based model, which has high accuracy and good performance. Finally, the frequency chart of tweets related to economy and their sentiment scores (positive and negative tweets) is plotted over time for the entire world and the top 10 economies. From the analysis of the charts, we learn that the reason for publishing economic tweets is not only the increase in the number of people infected with the Coronavirus but also imposed restrictions and lockdowns in countries. The consequences of these restrictions include the loss of millions of jobs and the economic downturn. © 2021 IEEE.

13.
JMIR Form Res ; 6(4): e31901, 2022 Apr 08.
Article in English | MEDLINE | ID: covidwho-1785266

ABSTRACT

BACKGROUND: HIV disproportionately impacts Black men who have sex with men (MSM), and targeting the primary relationship (ie, couples) using mobile technology for health holds promise for HIV prevention. Web-based recruitment of MSM is commonly employed in HIV prevention and intervention research. However, little known about recruiting Black MSM couples on the internet in the United States. OBJECTIVE: This study describes the process of recruiting Black MSM couples over social networking and dating apps frequented by MSM. We describe the activities for recruiting, screening, and enrolling participants as part of a randomized trial employing a multipronged recruitment approach. METHODS: Black MSM in couples were recruited via three apps (ie, Jack'd, Adam4Adam, and Growlr) between May 2020 and March 2021 during the COVID-19 pandemic in the United States. Black MSM couples were eligible if one or both partners are Black, MSM, and living with HIV, and if both partners were 18 years or older, and have been together for at least 2 months in what they both consider a primary relationship (ie, one in which both partners reported feeling most committed to over any other partner or relationship). RESULTS: A total of 10 Black MSM couples (n=20) were enrolled via social networking apps. App recruitment activities were a combination of passive (eg, in-app advertisements) and active (eg, direct messaging of users) engagement. Recruitment approaches varied by the social networking app owing to differences in app features. A full-time recruiter experienced challenges such as bugs (ie, technical errors in computer program or system), navigating technical requirements specific to each app, and web-based harassment. CONCLUSIONS: Despite challenges, it was possible to recruit Black MSM couples virtually into research as part of a multipronged recruitment strategy. We identify tips for using web-based dating and other social networking apps as part of a recruitment strategy in future research with Black MSM couples.

14.
Complexity ; 2022, 2022.
Article in English | ProQuest Central | ID: covidwho-1784922

ABSTRACT

The purpose of this paper is to investigate the impact of crude oil market structure on stock market volatility in Asian countries in the period 2008–2017. We integrate network analysis with the SGMM estimation technique to achieve the research objective. Network analysis was conducted with 43 Asian countries, while analysis of the impact of crude oil market structure on stock markets was performed with a sample of 19 countries. The results show that the stock market has a positive growth in countries with stronger export capacity while it is negatively affected in larger importing countries. In addition, the research results show that the stock market’s growth is greater in countries with a central position in the crude oil market. The study results will be useful for countries in reducing the undesirable impact of crude oil market on the stock market.

15.
55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 ; 2021-October:1302-1306, 2021.
Article in English | Scopus | ID: covidwho-1779140

ABSTRACT

Dynamic Bayesian Network (DBN) is an useful tool to learn the causal inference and social network of random variables. In this article, we analyze the correlations between the spread of coronavirus (COVID-19) and certain self-reported COVID-19 indicators in the United States, and then adopt DBN model with search and score-based approach to analyze and interpret the causal relationships and social network between these variables by learning the structure of the Directed Acyclic Graph from the model. We explore the change of causality among fifty states during the pandemic of COVID-19 in the year of 2020 and interpret the root cause for changes and trends. We concentrate on five worst states with COVID-19 and then extended our studies to all states by comparing the causal relationships and analyzing the patterns of DAG. © 2021 IEEE.

16.
2021 International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1779098

ABSTRACT

Pandemics originated by Covid-19 has caused many reactions in the world. Each country has reacted with different health policies. In this work, we analyze the publications of African citizens on Social networks (Twitter) to understand the pandemic scenario during the study period using a text mining approach. The study also adopted a statistical model to quantify the impact of daily COVID-19 cases on the frequency of tweets. Findings show that African tweets are related to awareness creation and policies to control the spread of COVID-19. © 2021 IEEE.

17.
Front Public Health ; 10: 819371, 2022.
Article in English | MEDLINE | ID: covidwho-1776013

ABSTRACT

Service industries contribute significantly to the economic, social, and even life aspect of the world. However, service innovation has been rarely discussed in healthcare context, especially in the digital healthcare context Service innovation needs to be organized in the premise of mutual trust to be efficient, thereby improving service performance. The trust and efficiency here demands a good online platform service to both virtualize the interaction processes and maintain trust and agency. This research uses social network theory and agency theory to emphasize the importance of trust in cooperation in hospitals, and the relationship between organizational trust and organizational performance. Furthermore, we analyzed the role of agents in enhancing the relationship between service innovation and trust. Based on the analyses, five propositions and future research directions are proposed.


Subject(s)
Delivery of Health Care , Trust , Hospitals , Humans , Social Networking
18.
Front Public Health ; 9: 750340, 2021.
Article in English | MEDLINE | ID: covidwho-1775932

ABSTRACT

Social isolation and loneliness in older adults are associated with poor health outcomes and have been linked to an increased risk of cognitive impairment and incident dementia. Social engagement has been identified as a key factor in promoting positive health behaviors and quality of life and preventing social isolation and loneliness. Studies involving cognitively healthy older adults have shown the protective effects of both in-person and technology-based social engagement. However, the benefits of social engagement for people who are already at-risk of developing dementia, namely those with mild cognitive impairment (MCI), have yet to be elucidated. We present a narrative review of the literature, summarizing the research on social engagement in MCI. First, we identified social networks (quality, size, frequency, and closeness) and social activities (frequency, format, purpose, type, and content) as two overarching dimensions of an integrative framework for social engagement derived from literature examining typical cognitive aging. We then used this framework as a lens to examine studies of social engagement in MCI to explore (i) the relationship between in-person and technology-based social engagement and cognitive, emotional, and physical health, and (ii) interventions that target social engagement including technology-based approaches. Overall, we found that persons with MCI (PwMCI) may have different levels of social engagement than those experiencing typical cognitive aging. Moreover, in-person social engagement can have a positive impact on cognitive, emotional, and physical health for PwMCI. With respect to activity and network dimensions in our framework, we found that cognitive health has been more widely examined in PwMCI relative to physical and emotional health. Very few intervention studies have targeted social engagement, but both in-person and technology-based interventions appear to have promising health and well-being outcomes. Our multidimensional framework of social engagement provides guidance for research on characterizing the protective benefits of social engagement for PwMCI and informs the development of novel interventions including technology-based approaches.


Subject(s)
Cognitive Dysfunction , Aged , Cognitive Dysfunction/psychology , Humans , Quality of Life , Social Participation , Technology
19.
International Journal of Public Health Science ; 11(1):69-76, 2022.
Article in English | Scopus | ID: covidwho-1776651

ABSTRACT

The spread of the coronavirus disesase 2019 (COVID-19) virus is relatively fast and has infected hundreds of countries. The number of people suffering from COVID-19 continues to increase and is increasingly concerning. To reduce the possibility of spreading the Coronavirus, which is easily contagious, the World Health Organization (WHO) advises the public to maintain a safe distance from other people through physical distancing. This study is a systematic review using the preferred reporting item for systematic reviews and meta-analyzes (PRISMA) method using 454 articles from online journal databases. The databases used in the literature search were Pubmed, Science Direct, Sage, Emerald, and Proquest from 2020-2021. Based on the inclusion and exclusion characteristics, there were 8 of 454 articles met the inclusion criteria, and select for in-depth analysis. Physical distancing policy has an impact on adolescent mental health. Some of the mental disorders experienced by adolescents include feeling lonely, anxious, stressed, psychiatric disorders, to emotional disturbances. Boys have a higher increase in mental health problems than girls. We need a social network and social support specifically in adolescents to maintain physical distancing during the adolescent mental health policy in the COVID-19. © 2022, Intelektual Pustaka Media Utama. All rights reserved.

20.
8th International and the 14th National Conference on e-Learning and e-Teaching, ICELET 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1774644

ABSTRACT

The Covid-19 pandemic in the world proved that the current style of education needs to be revised and reconsidered and the potentials of information technology should be further used in education. Understanding the attitude of users in using social networks seems to be highly important due to the increased use of online social networks. In this study, we targeted the evaluation of factors affecting students' intention to use social networks as an educational facilitating tool in the Covid-19 pandemic era based on the Davis Technology Acceptance Model (TAM) and other studies in this area. To this end, we first reviewed the literature to extract the factors affecting the intention of students to use social networks, based on which, the structural equations model was formed. This study was conducted among 200 students. The partial least squares structural equation modeling (PLS-SEM) technique was used to analyze the data. The findings analysis indicated the usefulness of the perceived use and perceived ease of use on the intention to use social networks. The results of this study provide fruitful insight into the use of social networks as an educational facilitation tool for policy-makers. © 2021 IEEE

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