Real-Time Infoveillance of Moroccan Social Media Users’ Sentiments towards the COVID-19 Pandemic and Its ManagementArticle Published on 2021-11-192022-10-29 Journal: International Journal of Environmental Research an [Category] COVID-19, MERS, SARS, [키워드] Analysis classical collected data COVID-19 COVID-19 mitigation dataset Dialect dominant Effects emotion Emotion analysis emotional events expressed Facebook Government identify Interaction language machine learning management media Model modeling Modern Standard Arabic Morocco outperform pandemic platform polar sentiment analysis protocol public health reaction Recognition Regulation respond significantly social distancing Topic topic modeling Universal universal language model for Moroccan dialect website [DOI] 10.3390/ijerph182212172 PMC 바로가기 [Article Type] Article
The State of Mind of Health Care Professionals in Light of the COVID-19 Pandemic: Text Analysis Study of Twitter DiscoursesOriginal Paper Published on 2021-10-222022-10-30 Journal: Journal of Medical Internet Research [Category] COVID-19, MERS, SARS, [키워드] accounted active learning affected Algorithm analyzed association Burnout Care caused changes in confirmed cases COVID-19 COVID-19 pandemic decrease defined described discourse distribution Effect Emotion analysis emotional exceeded expressed expressing extreme Factor fatigue fraction hcp Health Health care health care professionals Implications increase in indicate individual intensity labeling lack LIGHT long-lasting Longitudinal data longitudinal study machine learning mental health Mental health disorder mind morbidity MOST objective organization organizations pandemic pathway Population Prevent professional profiles resource Result sentiment analysis social media Spearman correlation coefficient state Support text timeline Topic topic analysis Twitter Volume was selected [DOI] 10.2196/30217 PMC 바로가기 [Article Type] Original Paper
Revealing Public Opinion Towards COVID-19 Vaccines With Twitter Data in the United States: Spatiotemporal PerspectiveOriginal Paper Published on 2021-09-102022-10-30 Journal: Journal of Medical Internet Research [Category] COVID-19, SARS, [키워드] accompanied Analysis analyzed benefit changes changes in collected Community COVID-19 COVID-19 pandemic COVID-19 vaccine COVID-19 vaccines decrease Defense driver effective intervention Emotion analysis event examined Factor global efforts help identify Impact individual information International investigated mechanism media MONITOR National objective opinion pandemic positive promote Public public health public health authority public health crisis public opinion Result rising sentiment analysis spatiotemporal the United State The United States the vaccine Topic topic modeling Twitter Vaccine Vaccines [DOI] 10.2196/30854 PMC 바로가기 [Article Type] Original Paper
EMOCOV: Machine learning for emotion detection, analysis and visualization using COVID-19 tweetsResearch article Published on 2021-05-012022-10-05 Journal: Online Social Networks and Media [Category] 치료기술, [키워드] Accuracy activity affecting Analysis automatically changed coronavirus COVID-19 COVID-19 data data analytics dataset detect develop Emotion analysis emotional Health lockdown machine machine learning mental health negative outperform pandemic physically response responsible selected Topics tracker Twitter Data USA [DOI] 10.1016/j.osnem.2021.100135 [Article Type] Research article
Measuring the Outreach Efforts of Public Health Authorities and the Public Response on Facebook During the COVID-19 Pandemic in Early 2020: Cross-Country ComparisonOriginal Paper Published on 2020-05-192022-10-30 Journal: Journal of Medical Internet Research [Category] COVID-19, MERS, SARS, [키워드] Analysis analyzed approach authority CDC center Control coronavirus disease COVID-19 COVID-19 pandemic CPP disease disseminate effort Emotion analysis England event Facebook Frequency Health authority help highest highlighting IMPROVE increasingly Infectious disease information measure media Metrics Ministry of Health negative emotion objective outbreak Outbreaks outreach pandemic per day PHA PHE positive prevalent prevention Public public engagement public health public health authorities Public Health England reaction response Result sentiment analysis Singapore social media The United States toxic trend understanding virus was performed were measured [DOI] 10.2196/19334 PMC 바로가기 [Article Type] Original Paper