ABSTRACT
Words can shift their meaning across time. This case study shows the results obtained by the exploratory analysis of the semantic shifting on Spanish vocabulary using Diachronic Words Embeddings. Diachronic data consists of a 2018 Spanish corpus, before the COVID-19 outbreak, and a second corpus with documents from 2021. We focused on the semantic shift of three of the topics: COVID-19, masks and vaccines. This paper addresses the construction of the diachronic Spanish word embeddings model, as well as the results obtained by the analysis using a non-supervised distance vector technique. The results allowed to identify shifts related to increase in COVID-19 content. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic caused an unprecedented crisis in the higher education sector through campuses closing worldwide. To contain the disease, authorities required their citizens to wear facemasks in public spaces. As universities return to in-person instruction, they will probably require all students to wear facemasks while on-campus. This study examined antecedents of voluntary adoption of facemasks through a survey of students enrolled in Mexico City universities in the Fall of 2020. It was hypothesized that Social Value Orientation (SVO) and Trust would be positively related to facemask adoption. Findings revealed that among students, wearing a facemask reflects distinct conducts depending on the social context. Regression results show that SVO and Trust significantly predict facemask use but only in some contexts, giving partial support to hypotheses. A key implication is that public health communications should avoid general messages recommending facemasks, and craft more nuanced appeals targeting specific social contexts. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The World Health Organization (WHO) declared SARS-CoV-2, the cause of COVID-19, the coronavirus disease as a global pandemic [1] that affects millions of people due to its high rate of spread and its severity. So far, COVID-19 has reached almost every country in the world with no effective treatment or vaccine to eradicate it. The growing and accelerated curve of infections of Covid-19 has brought with it innumerable problems, and this has triggered zonal governments to establish prevention and control mechanisms, such as quarantines, closings of establishments with influxes of people, including schools, colleges, cinemas, gyms, among others, triggering a severe stopping in economic activities [2]. The aforementioned leads to an emotional alteration of people due to the uncertainty caused by this pandemic, the use of computer applications oriented to e-health or telemedicine (use of information and communication technologies in the area of medicine) today allows in a certain way to control health care and allows application users to enter data on the symptoms presented and recommend prevention and control treatments for those symptoms, being useful for patients as it helps to mitigate their anxiety. The present research is based on the analysis of 97 existing mobile applications used for the control and monitoring of the disease COVID-19 caused by SARS-CoV-2 virus, evaluating the characteristics presented by each one, both for the Android and iOS operating systems. The Scoping methodology was adapted in order to identify the reseach question, select the relevant applications, plot the data, compare, summarize and present the findings. © 2020, Springer Nature Switzerland AG.