ABSTRACT
In this study, Turkish and English tweets through Twitter Application Program Interface (API) between 1-31 January 2021 are analyzed with respect to Covid-19. The collected tweets are preprocessed, labeled with the Vader Sentiment library, and then analyzed by topic modeling with Nonnegative Matrix Factorization. The analysis show that the most frequently mentioned word is “vaccine/aşı” after “Covid”. The topics modelled in the study are grouped into themes and the themes are seen to be similar in both languages, which means that the Turkish and world agenda are not very different in terms of themes in pandemics. Moreover, hypothesis tests are conducted to understand whether language and time period are related to sentiment class. The results show that the Turkish people are more neutral about the Covid-19 issue than other people in the world during the given period of time. Moreover, independent of the language, there are more negative and neutral tweets in the first half of January 2021, whereas there are more positive tweets in the second half of the month. To the best of our knowledge, this is the first study to analyze Covid-19 related tweets in two languages to compare the local and global agendas using topic modeling, sentiment analysis, and hypothesis testing methods. © 2022 Kauno Technologijos Universitetas. All rights reserved.
ABSTRACT
The outbreak of SARS-CoV-2 has emphasized the value of point-of-care diagnostics, as well as reliable and cost-effective serological antibody tests, to monitor the viral spread and contain pandemics and endemics. Here, we present a three-dimensional (3D) nanofluidic device for rapid and multiplexed detection of viral antibodies. The device is made from poly(methyl methacrylate) and contains 3D fluidic channels with nanoscale topography variations on the millimeter length scale, enabled by combining gray-scale e-beam lithography and nanoimprint lithography. It works with capillary pumps only and does not require a complex microfluidic setup and pumps, which hinder the widespread usage of micro- and nanofluidic devices. The device is designed to size dependently immobilize particles from a multiparticle mixture at predefined positions in nanochannels, resulting in distinct trapping lines. We show that it can be used as an on-chip fluorescence-linked immunosorbent assay for highly specific and sensitive multiplexed detection of serological antibodies against different viral proteins. Further test flexibility is demonstrated by on-bead color multiplexing for simultaneous detection of IgG and IgM antibodies in convalescent human serum. The particle sorting is further leveraged to enable concurrent detection of anti-spike (SARS-CoV-2) and anti-hemagglutinin (influenza A) antibodies. The device's applications can be further extended to detect a large variety of diseases simultaneously in a reliable and straightforward manner.