A Report on the Impact of Information Technology and Social Media on Covid–19

Sathish, Rachana; Ramesh, Manikandan; Priscila, Sara; Sara, Belina Vj; Mahaveerakannan, R.

doi:10.1109/iciss49785.2020.9316046

Cited by 62 publications

(17 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Moreover, due to the rising use of IT platforms and increase usage of the internet, a substantial shift has been observed in usage patterns and behaviors. People who work in the field of business, society, or government have been adapting quickly to new "styles"-with interactive online meetings, shifting office-based to home tasking with new emerging technologies, and adopting behavioral and usage patterns (Sathish et al 2020). China has observed the changes in the consumers' behavior in food purchasing and consumption during COVID-19.…”

Section: Introductionmentioning

confidence: 99%

Consumer usage behavior of internet-based services (IBS) in Pakistan during COVID-19 crisis from the perspective of technology acceptance model

Ishfaq

Huang

2021

Environ Sci Pollut Res

View full text Add to dashboard Cite

This study aims to explore the factors that affect consumers’ behavior in adaptation and use of internet-based services (IBS) during the COVID-19 crisis. In this study, technology acceptance model (TAM) was applied to predict the behavioral intention of active social media users among the Pakistan population based on the revised model of the TAM model. And the data of external factors facilitating conditions (FC), social impact (SI), and task technology fit (TTF) were collected from active social media users of Pakistan by using structured questionnaires. After performing Pearson’s correlation and linear regression on the collected data, findings have shown that the outcome variable, i.e., behavioral intention, exhibited significant correlation with all variables except for perceived ease of use (PEoU). Further analysis revealed mixed results wherein FC and TTF can make a significant influence on perceived usefulness (PU) and PEoU, respectively. In addition, PU can significantly affect attitude (ATT) towards the use of IBS while the use of IBS has been affected by behavioral INT during the outbreak of COVID-19 in Pakistan.

show abstract

Section: Introductionmentioning

confidence: 99%

Consumer usage behavior of internet-based services (IBS) in Pakistan during COVID-19 crisis from the perspective of technology acceptance model

Ishfaq

Huang

2021

Environ Sci Pollut Res

View full text Add to dashboard Cite

show abstract

“…The purpose of this research can be initiated by collecting the real-time symptom data using wearable sensors set located in the patient's body [23]. The previous study discusses the most significant COVID-19 symptoms which are identified from the real COVID-19 patient dataset.…”

Section: Data Collection About Symptomsmentioning

confidence: 99%

Predictive Machine Learning (Ml) Algorithm Using Iot Framework for Novel Corona Virus (Covid-19)

Murthy¹

2021

pae

View full text Add to dashboard Cite

During earlier months of the pandemic COVID-19 with no recommended cure or vaccine available only solution to destroy the chain is self-isolation which can be maintained by physical distancing. This is now understood that the world require much faster solution to accommodate and deal with the future COVID-19 spread over the world by non-clinical methods namely data mining, augmented intelligence and several Artificial Intelligence (AI) techniques. It has become a huge hindrance to mitigate for the healthcare industry to provide more potential involved for patient's diagnosis and also for effective prognosis of 2019-CoV pandemic. Therefore, the proposed framework is implemented with the Internet of Things (IoTs) in healthcare industry for collecting the symptom data of real-time that is beneficial in predicting whether the person gets infected with COVID-19 virus or not. This can be done through various signs namely body temperature, blood oxygen level, headache, coughing patterns, etc. Thus, the research work focused on faster identification of COVID-19 virus infection cases potentially using Machine Learning (ML) algorithm from the real-time symptom data. Moreover, the obtained results have illustrated that K-Nearest Neighbour (KNN) algorithm is highly efficient while compared with other ML algorithms such as Naive Bayes and Logistic Regression (LR) in predicting the possible recovery of the infected patients from pandemic COVID-19 with the accuracy of 96.85%.

show abstract

“…However, the researcher collected her data in 2018, which was before the Covid-19 lockdown, and she recommends more research on the effects of social media on students from various academic institutions. Many researchers and reports confirm that Covid-19 lockdowns have changed people's behavior (Jia, 2021;Koh, Pan, Shoesmith, James, Nor, Loo, 2020;Sathish, Manikandan, Silvia Priscila & Mahaveerakannan, 2020). Therefore, this study investigates the use and effects of social media platforms, namely Arab World English Journal www.awej.org ISSN: 2229-9327 206 Facebook, Twitter, and Instagram, on Kurd EFL learners after Covid-19 lockdowns in the region using learners from various academic institutions and different levels.…”

Section: Literature Reviewmentioning

confidence: 99%

Pedagogical Effects of Social Media on Iraqi Kurd EFL learners

Nuri¹,

Aziz²,

Saeed³

et al. 2021

AWEJ

View full text Add to dashboard Cite

English language learners use social media platforms for improving their language skills through exchanging ideas, sharing their thoughts, and getting exposed to authentic language. The use of social media by learners might yield positive or adverse effects. This study, therefore, explores the pedagogical consequences of some social media platforms on Iraqi Kurd EFL learners. It Highlights the significant impacts of social media on learning English, vocabulary, and spelling. It explicitly attempts to discover how social media affects English language learning, word choices, and spelling for Kurd EFL learners. A questionnaire is used to randomly collect the study data from 96 Kurdish students studying English at various academic institutions. The data was organized and analyzed by SPSS. It was found that Kurd EFL learners use social media platforms extensively for numerous purposes, improving their English language skills being one of them. The results suggest that social media assists learners in learning and practising new vocabulary; However, it has a negative impact on the students spelling and academic writing skills. Kurd EFL learners use abbreviated forms and unnecessarily shortened forms under the influence of social media.

show abstract

A Report on the Impact of Information Technology and Social Media on Covid–19

Cited by 62 publications

References 8 publications

Consumer usage behavior of internet-based services (IBS) in Pakistan during COVID-19 crisis from the perspective of technology acceptance model

Consumer usage behavior of internet-based services (IBS) in Pakistan during COVID-19 crisis from the perspective of technology acceptance model

Predictive Machine Learning (Ml) Algorithm Using Iot Framework for Novel Corona Virus (Covid-19)

Pedagogical Effects of Social Media on Iraqi Kurd EFL learners

Contact Info

Product

Resources

About