ABSTRACT
The COVID-19 pandemic has accelerated digital transformations across industries, but also introduced new challenges into workplaces, including the difficulties of effectively socializing with colleagues when working remotely. This challenge is exacerbated for new employees who need to develop workplace networks from the outset. In this paper, by analyzing a large-scale telemetry dataset of more than 10,000 Microsoft employees who joined the company in the first three months of 2022, we describe how new employees interact and telecommute with their colleagues during their "onboarding"period. Our results reveal that although new hires are gradually expanding networks over time, there still exists significant gaps between their network statistics and those of tenured employees even after the six-month onboarding phase. We also observe that heterogeneity exists among new employees in how their networks change over time, where employees whose job tasks do not necessarily require extensive and diverse connections could be at a disadvantaged position in this onboarding process. By investigating how web-based people recommendations in organizational knowledge base facilitate new employees naturally expand their networks, we also demonstrate the potential of web-based applications for addressing the aforementioned socialization challenges. Altogether, our findings provide insights on new employee network dynamics in remote and hybrid work environments, which may help guide organizational leaders and web application developers on quantifying and improving the socialization experiences of new employees in digital workplaces. © 2023 ACM.
ABSTRACT
Due to multiple COVID-19 lockdowns, individuals likely engaged in multiple activities, including viewing adult content. Even though a subscription-based pornographic content sharing (SPCS) website (e.g., OnlyFans or Fancentro) is operationally distinct from traditional sexual channels (e.g., Pornhub or Xvideos), no study has examined whether COVID-19 increased the visiting behaviors of these SPCS websites. Consequently, we attempted to address this void. The subscription to comScore services by Chulalongkorn Business School allowed us to utilize actual visitor behavior at three SPCS websites before and during COVID-19. The analysis of 17,477 visit sessions revealed that (1) pageviews and visit duration peaked before the pandemic, but (2) the average length of stay per pageview increased during the pandemic compared to before its introduction. In addition to providing theoretical insight into the relationship between COVID-19 and website-visiting behaviors of SPCS, our findings offer practical contributions. © 2023, International Journal of Economics and Finance Studies. All Rights Reserved.
ABSTRACT
Fact-checking messages are shared or ignored subjectively. Users tend to seek like-minded information and ignore information that conflicts with their preexisting beliefs, leaving like-minded misinformation uncontrolled on the Internet. To understand the factors that distract fact-checking engagement, we investigated the psychological characteristics associated with users' selective avoidance of clicking uncongenial facts. In a pre-registered experiment, we measured participants' (N = 506) preexisting beliefs about COVID-19-related news stimuli. We then examined whether they clicked on fact-checking links to false news that they believed to be accurate. We proposed an index that divided participants into fact-avoidance and fact-exposure groups using a mathematical baseline. The results indicated that 43% of participants selectively avoided clicking on uncongenial facts, keeping 93% of their false beliefs intact. Reflexiveness is the psychological characteristic that predicts selective avoidance. We discuss susceptibility to click bias that prevents users from utilizing fact-checking websites and the implications for future design. © 2023 Owner/Author.
ABSTRACT
During the COVID-19 pandemic, point-of-care genetic testing (POCT) devices were used for on-time and on-site detection of the virus, which helped to prevent and control the spread of the pandemic. Smartphones, which are widely used electronic devices with many functions, have the potential to be used as a molecular diagnostic platform for universal healthcare monitoring. Several integrated diagnostics platforms for the real-time and end-point detection of COVID-19 were developed using the functions of smartphones, such as the operating system, power, sound, camera, data storage, and display. These platforms use the 5V output power of smartphones, which can be amplified to power a micro-capillary electrophoresis system or a thin-film heater, and the CMOS camera of smartphones can capture the color change during a colorimetric loop-mediated isothermal amplification test and detect fluorescence signals. Smartphones can also be used with self-written web-based apps to enable automatic and remote pathogen analysis on POCT platforms. Our lab developed a handheld micro-capillary electrophoresis device for end-point detection of SARS-CoV-2, as well as an integrated smartphone-based genetic analyzer for the qualitative and quantitative colorimetric detection of foodborne pathogens with the help of a custom mobile app. © 2023 SPIE.
ABSTRACT
Recently, the COVID-19 pandemic has emerged as one of the world's most critical public health concerns. One of the biggest problems in the present COVID-19 outbreak is the difficulty of accurately separating COVID-19 cases from non-COVID-19 cases at an affordable price and in the initial stages. Besides the use of antigen Rapid Test Kit (RTK) and Reverse Transcription Polymerase Chain Reaction (RT-PCR), chest x-rays (CXR) can also be used to identify COVID-19 patients. Unfortunately, manual checks may produce inaccurate results, delay treatment or even be fatal. Because of differences in perception and experience, the manual method can be chaotic and imprecise. Technology has progressed to the point where we can solve this problem by training a Deep Learning (DL) model to distinguish the normal and COVID-19 X-rays. In this work, we choose the Convolutional Neural Network (CNN) as our DL model and train it using Kaggle datasets that include both COVID-19 and normal CXR data. The developed CNN model is then deployed on the website after going through a training and validation process. The website layout is straightforward to navigate. A CXR can be uploaded and a prediction made with minimal effort from the patient. The website assists in determining whether they have been exposed to COVID-19 or not. © 2023 IEEE.
ABSTRACT
This study serves as a follow-up on a 2020 study by Wang and Lund that examined the policy changes and announcement information provided by American public libraries during the early weeks of the coronavirus (COVID-19) pandemic, using the same list of libraries as the 2020 study to examine how the COVID response evolved over the past two years. Seven types of information were collected from the public libraries' websites, with the help of the Internet Archive to collect specific dates: frequency of announcement updates, date of start curbside/pickup services, date of reopening libraries, dates of posting vaccine-related information, dates of removal of COVID-19 related information, and dates of reopening face-to-face programs. The findings indicate that the timing of COVID response updates varied based on factors including the size of the municipality in which the public library is located and the political leaning of the municipality's voters. [ FROM AUTHOR] Copyright of Public Library Quarterly is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
The U.S. Department of State recognizes that students "act as citizen ambassadors by building relationships within their host communities, demonstrating American values, and debunking stereotypes" (U.S. Department of State, 2023). According to the GAPP website, over 750 high schools in the United States have a GAPP program and more than 9000 students participate in GAPP each year. Afterwards, the students filled out an evaluation of GAVE, provided on the GAVE website. Ludwig confirms that "online classes cannot replace the classical purpose of a stay abroad, namely: to be in a different place, in a different environment, to gain hands-on experience and, last but not least, to become more independent" (Ludwig, 2022).
ABSTRACT
This study investigates the factors that might have affected the implementation of the mask-wearing measure in Greek society from March 2020 to November 2021. To do so, this study utilizes a critical review of dominant characteristics of modern Greek society followed by a systematic review of the most recent literature on mask-wearing attitudes. The data in this study is derived from official Greek governmental announcements regarding the mask-wearing measure during the pandemic and the depiction of attitudes towards mask-wearing through Greek digital media, including digital newspapers, informative magazines and websites, and digital news sites. The article argues that the main preventive factors relate to distrust towards authority, including specific identified barriers according to relevant literature. More importantly, this study reinforces the significance of the adequate appreciation of the historical, cultural and social context within which political measures are implemented regardless of their global scale and universal necessity. [ FROM AUTHOR] Copyright of Journal of Southeast European & Black Sea Studies is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Determining sentiments of the public with regard to COVID-19 vaccines is crucial for nations to efficiently carry out vaccination drives and spread awareness. Hence, it is a field requiring accurate analysis and captures the interest of many researchers. Microblogs from social media websites such as Twitter sometimes contain colloquial expressions or terminology difficult to interpret making the task a challenging one. In this paper, we propose a method for multi-label text classification for the track of”Information Retrieval from Microblogs during Disasters (IRMiDis)” presented by the”Forum of Information Retrieval Evaluation” in 2022, related to vaccine sentiment among the public and reporting of someone experiencing COVID-19 symptoms. The following methodologies have been utilised: (i) Word2Vec and (ii) BERT, which uses contextual embedding rather than the fixed embedding used by conventional natural language models. For Task 1, the overall F1 score and Accuracy are 0.503 and 0.529, respectively, placing us fourth among all the teams, while for Task 2, they are 0.740 and 0.790, placing us second among all the teams who submitted their work. Our code is openly accessible through GitHub. 1 © 2022 Copyright for this paper by its authors.
ABSTRACT
PurposeThis study investigates how customer experience mediates the relationship between online innovation and repurchase intention in the hotel industry in Ghana.Design/methodology/approachData was collected from 167 clients from a two-star hotel in Accra, the capital city of Ghana. Structural equation modelling was used to analyse the relationship between the variables.FindingsResults from the analysis indicate that online innovation positively leads to higher repurchase intentions and better customer experience, affirming that customer experience leads to repurchase intentions. Thus, while online innovation leads to repurchase intentions, the strength of this repurchase intention depends on customer experience. Therefore, customer experience mediates the relationship between online innovation and repurchase intention in the hotel industry.Research limitations/implicationsThis study addressed only the customer's point of view;future studies could investigate the subject from the managers and other stakeholders' point of view to get a holistic view. Also, the sample size could be improved, and the study could be conducted in other African countries for comparison purposes.Practical implicationsThe study shows that online innovation does not automatically lead to increased positive repurchase intention. Hotel managers must, therefore, enforce good customer experience for better profitability.Originality/valueAs far as the researchers know, limited studies have been conducted into how customer experience mediates online innovation and repurchase intention in the hotel industry in Ghana using structural equation modelling. This makes this research unique in Ghana. This study makes an original contribution by measuring the real effect of innovation on repurchase intentions in the hotel industry in Ghana.
ABSTRACT
Due to the COVID-19 pandemic, the demand for distance learning has significantly increased in higher education institutions. This type of learning is usually supported by Web-based learning systems such as Massive Open Online Courses (Coursera, edX, etc.) and Learning Management Systems (Moodle, Blackboard-Learn, etc.). However, in this remote context, students often lack feedback and support from educational staff, especially when they face difficulties or challenges. For that reason, this work presents a Prediction-Intervention approach that (a) predicts students who present difficulties during an online learning course, based on two main learning indicators, namely engagement and performance rates, and (b) offers immediate support to students, tailored to the problem they are facing. To predict students' issues, our approach considers ten machine learning algorithms of different types (standalone, ensemble, and deep learning) which are compared to determine the best performing ones. It has been experimented with a dataset collected from the Blackboard-Learn platform utilized in an engineering school called ESIEE-IT in France during 2021-2022 academic year, showing thus quite promising results. © 2022 IEEE.
ABSTRACT
Open source Geographic Information System (GIS) have been fostering spatial data research such as Earth observation and environmental monitoring for more than 30 years. More recently, globally available geospatial information combined with web technologies are providing new environments and tools for data handling. Thus, binding the mapping and processing capabilities of traditional GIS to the accessibility and reliability of web-based data providers can bring new opportunities for research. In this paper, we built a QGIS plugin to explore the integration of different public data providers in Brazil along with field data produced by the BONDS project. The biOdiversity conservatioN with Development in Amazon wetlandS project (BONDS) proposes to develop biodiversity scenarios for the Amazonian floodplains aiming to support solutions to preserve biodiversity and ecosystem services. The use of web services enabled dynamic and fast access to several products ranging from remote sensing images, land use and land cover, territorial cartography, water quality, to COVID-19 health data, and more. © 2022 National Institute for Space Research, INPE. All rights reserved.
ABSTRACT
Choosing a proper outfit is one of the problems we deal with every day. Today, people tend to use online websites for shopping, and the COVID-19 situation forced this condition more than before. In this research, we proposed a new architecture for multi-fashion item retrieval from a website database. We deployed a CLIP transformer model instead of convolutional neural networks in a triplet network. We also added a long short-term memory network (LSTM) to automatically extract and code the image features to generate descriptive text for each input image. Our OutCLIP model succeeded in doing its task with 83% precision and 85% recall accuracy in multi-item retrieval. This model can be trained and used in fashion retrieval problems and improve the former proposed models. Considering the descriptive text and the image together gives the model a better understanding of the concept and improves its generalization. © 2023 IEEE.
ABSTRACT
All the nations' administrative units are concerned about the COVID-19 outbreak in different regions of the world. India is also trying to control the spread of the virus with strict measures and has managed to slow down its growth rate. The administration of each country faces the challenge of maintaining records of corona patients. To address this challenge, this work builds a website from scratch using real-time APIs for data visualization. The website provides information on the number of active cases, death cases, recovery cases, and total cases of COVID-19 patients in each country. The data can be visualized using graphs, making it easier to compare the situation in different countries. The website allows for monitoring which country has a higher number of deaths, patients, favorable recovery rates, and a large number of active cases. The COVID-19 status regarding patients can be analyzed through graphical representation using real-time data. © 2023 IEEE.
ABSTRACT
During Covid-19 pandemic many people and institutions preferred online coaching instead of in person education. The problem with online is that it will be difficult to carry on interconnections between students and professors in that environment. The main constraint for conducting online session is that the people in remote areas may find a difficulty to connect to online sessions having network issues. Electronic mentoring (e-mentoring) is implemented like a website in which the mentor and mentee can communicate with each other. With the help of this mentoring the project can provide a best solution for both the mentor and mentee. They can communicate with each other with the help of online platform and even with the help of emails.This proposed method will help them to keep the track of their academic progress and achievements of students. This article mainly focus on the mentoring through physical and virtual environment in which the mentee will be interacting with the mentor to know the progress of their academics. This article discusses about the website which is developed to fulfill the needs of the student and it discusses about the various stages of development that helped in building the website. Students can share their difficulties and their achievements with the mentor who are assigned for them particularly. In future planning to implement artificial intelligence technique to online mentoring process, this is for the betterment of student's growth. © 2023 IEEE.
ABSTRACT
In this article, we present Ear Talk – a co-composition and live performance project that enables remote music collaboration through technologically mediated systems. The Ear Talk project currently exists in two distinct implementations, one that repurposes YouTube's live-streaming technology, and one that utilises a stand-alone website. Although Ear Talk was conceived prior to the 2020 COVID-19 pandemic, the necessity for remote collaboration became more apparent during the lockdown, when a vast majority of live events and music concerts were cancelled. The Ear Talk project enables a socially distanced form of online musical collaboration and offers a platform through which to respond to such a crisis, and has grown to be adopted and presented by many different performing groups across the world. In addition to describing the technical implementations of these two systems, we discuss issues that arise from our participatory practice: from musical quality concerns in regard to social aesthetics and artistic ingenuity, to accessibility concerns when designing technologically mediated collaborative systems. Ear Talk embraces continuous musical loops as well as highly asynchronous (i.e., perpetual) collaborative paradigms among remote participants, which raises a conceptual inquiry as to which part of its sonic and social experience constitutes music in the end. Finally, we evaluate performer–audience relationships (i.e., hierarchical versus horizontal interactions) and the efficacy of the Ear Talk systems at enabling socially engaged co-composition.
ABSTRACT
In early March, the newspapers reported the arrival of the Coronavirus in Brazil. The period of confinement directly affected our routines and transformed our consumption habits. Amidst the fear of contagion and uncertainty, people isolated themselves and postponed changes. Previous studies indicate that digital practices were accelerated after the onset of the COVID-19 pandemic, facilitating communication and improving the performance of various sectors of the economy. Thus, to better understand the behavior of Brazilian real estate market professionals in this period, the objective of this research was to verify whether the COVID-19 pandemic accelerated the process of perception of digitalization in real estate websites. To this end, five experts in the digital real estate market were interviewed, asked what are the main items that a quality real estate website should have to improve user experience. Based on the items selected by the experts, a questionnaire was developed and a question was constructed for each item. The questionnaire was sent online to 2144 realtors, asking about the importance of these items before and after the pandemic started. Using a 5-point Likert scale, and strict criteria for analysis, our survey yielded 423 valid responses. The results indicate that regardless of the groups analyzed, the hypotheses confirm that after the beginning of the COVID-19 pandemic, the perception of the importance of digital technology in Brazilian real estate websites was enhanced, increased. Managers took advantage of the pandemic and the availability of digital technology to offer specialized service to customers, thus creating a new competitive scenario. The tools associated with the visualization of the property and information such as '360°/Video Tour', 'Video Visit Broadcast', 'Chatbots' and 'FAQ List' had the greatest increase in perception.
ABSTRACT
The Dyrosauridae Hyposaurus derbianus Cope was loaned by Orville A. Derby in 1880 to Edward D. Cope to be studied. After Cope's death the specimens were not returned and toured several foreign institutions like the American Museum of Natural History in New York and the National History Museum (NHM) in London. We accessed several documents of the Memory and Archive Sector of the National Museum of Brazil (Museu Nacional/Universidade Federal do Rio de Janeiro) to elucidate the real trajectory of the H. derbianus holotype. We noticed several errors in the literature, going from the assignment of the specimen as a syntype, even though it is a holotype according to the ICZN, to registration number problems. In addition, photographs of specimen PV R 8672, previously taken at the NHM, describing it as a cast of H. derbianus in the NHM's official website, were correlated with the original material studied by Cope and recognised through the labels of the Museu Nacional/UFRJ and the Geological Commission of the Brazilian Empire (Comissão Geológica do Império). Lastly, despite the fire at the Museu Nacional/UFRJ and the limitations imposed by the COVID-19 pandemic, we were able to locate the holotypes at the NHM and elucidate its history.
ABSTRACT
The purpose of this study was to prove the use of content and sentiment analysis to understand public discourse on Nytimes.com around the coronavirus (2019-nCOV) pandemic. We examined the pandemic discourses in the article contents, news, expert opinions, and statements of official institutions with natural language processing methods. We analyzed how the mainstream media (Nytimes.com) sets the community agenda. As a method, the textual data for the research were collected with the Orange3 software text-mining tool via the Nytimes.com API, and content analysis was conducted with Leximancer software. The research data were divided into three categories (first, mid, and last) based on the date ranges determined during the pandemic. Using Leximancer concept maps tools, we explained concepts and their relationships by visualizing them to show pandemic discourse. We used VADER sentiment analysis to analyze the pandemic discourse. The results gave us the distance and proximity positions of themes related to Nytimes.com pandemic discourse, revealed according to their conceptual definitions. Additionally, we compared the performance of six machine learning algorithms on the task of text classification. Considering the findings, it is possible to conclude that in Nytimes.com (2019-nCOV) discourse, some concepts have changed on a regular basis while others have remained constant. The pandemic discourse focused on specific concepts that were seen to guide human behavior and presented content that may cause anxiety to readers of Nytimes.com. The results of the sentiment analysis supported these findings. Another result was that the findings showed us that the contents of the coronavirus (2019-nCOV) articles supported official policies. It can be concluded that regarding the coronavirus (2019-nCOV), which has caused profound societal changes and has results such as death, restrictions, and mask use, the discourse did not go beyond a total of 15 main themes and about 100 concepts. The content analysis of Nytimes.com reveals that it has behavioral effects, such as causing fear and anxiety in people. Considering the media dependency of society, this result is important. It can be said that the agenda-setting of society does not go beyond the traditional discourse due to the tendency of individuals to use newspapers and news websites to obtain information.
ABSTRACT
The abundance of library associations provides many choices to academic librarians about where and how to belong. This exploratory article identifies and compares benefits of library professional organizations through content analysis of the groups' websites. Examination of the benefits described on the websites of 76 organizations indicates that they have a high degree of overlap. Many benefits are also achievable by participating in other external professional activities. While data were collected just prior to the start of the COVID-19 pandemic, thematic analysis of these benefits provides a framework for comparing the value of participation in formal and informal professional communities.