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10.2196/19276 http://scihub22266oqcxt.onion/10.2196/19276 32421686!7304257!32421686     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       JMIR+Public+Health+Surveill 2020 ; 6 (2): e19276 Nephropedia Template TP {{tp|p=32421686|t=2020. Mining Physicians Opinions on Social Media to Obtain Insights Into COVID-19: Mixed Methods Analysis |pdf=|usr=}}{{32421686}} gab.com Text Mining Physicians Opinions on Social Media to Obtain Insights Into COVID-19: Mixed Methods Analysis JO: JMIR Public Health Surveill http://www.kidney.de/pget.php?&tw=1&pmid=32421686 #FOAvip BACKGROUND: The coronavirus disease (COVID-19) pandemic is considered to be the most daunting public health challenge in decades. With no effective treatments and with time needed to develop a vaccine, alternative approaches are being used to control this pandemic. OBJECTIVE: The objective of this paper was to identify topics, opinions, and recommendations about the COVID-19 pandemic discussed by medical professionals on the Twitter social medial platform. METHODS: Using a mixed methods approach blending the capabilities of social media analytics and qualitative analysis, we analyzed COVID-19-related tweets posted by medical professionals and examined their content. We used qualitative analysis to explore the collected data to identify relevant tweets and uncover important concepts about the pandemic using qualitative coding. Unsupervised and supervised machine learning techniques and text analysis were used to identify topics and opinions. RESULTS: Data were collected from 119 medical professionals on Twitter about the coronavirus pandemic. A total of 10,096 English tweets were collected from the identified medical professionals between December 1, 2019 and April 1, 2020. We identified eight topics, namely actions and recommendations, fighting misinformation, information and knowledge, the health care system, symptoms and illness, immunity, testing, and infection and transmission. The tweets mainly focused on needed actions and recommendations (2827/10,096, 28%) to control the pandemic. Many tweets warned about misleading information (2019/10,096, 20%) that could lead to infection of more people with the virus. Other tweets discussed general knowledge and information (911/10,096, 9%) about the virus as well as concerns about the health care systems and workers (909/10,096, 9%). The remaining tweets discussed information about symptoms associated with COVID-19 (810/10,096, 8%), immunity (707/10,096, 7%), testing (605/10,096, 6%), and virus infection and transmission (503/10,096, 5%). CONCLUSIONS: Our findings indicate that Twitter and social media platforms can help identify important and useful knowledge shared by medical professionals during a pandemic. Twit Text FOAVip Mining Physicians Opinions on Social Media to Obtain Insights Into COVID-19: Mixed Methods Analysis ????JMIR Public Health Surveill http://www.kidney.de/pget.php?&tw=1&pmid=32421686 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32421686 #FOAvip English Wikipedia <ref>{{Cite pmid|32421686}}</ref> Mining Physicians Opinions on Social Media to Obtain Insights Into COVID-19: Mixed Methods Analysis #MMPMID32421686 Wahbeh A; Nasralah T; Al-Ramahi M; El-Gayar O JMIR Public Health Surveill 2020[Jun]; 6 (2): e19276 PMID32421686show ga BACKGROUND: The coronavirus disease (COVID-19) pandemic is considered to be the most daunting public health challenge in decades. With no effective treatments and with time needed to develop a vaccine, alternative approaches are being used to control this pandemic. OBJECTIVE: The objective of this paper was to identify topics, opinions, and recommendations about the COVID-19 pandemic discussed by medical professionals on the Twitter social medial platform. METHODS: Using a mixed methods approach blending the capabilities of social media analytics and qualitative analysis, we analyzed COVID-19-related tweets posted by medical professionals and examined their content. We used qualitative analysis to explore the collected data to identify relevant tweets and uncover important concepts about the pandemic using qualitative coding. Unsupervised and supervised machine learning techniques and text analysis were used to identify topics and opinions. RESULTS: Data were collected from 119 medical professionals on Twitter about the coronavirus pandemic. A total of 10,096 English tweets were collected from the identified medical professionals between December 1, 2019 and April 1, 2020. We identified eight topics, namely actions and recommendations, fighting misinformation, information and knowledge, the health care system, symptoms and illness, immunity, testing, and infection and transmission. The tweets mainly focused on needed actions and recommendations (2827/10,096, 28%) to control the pandemic. Many tweets warned about misleading information (2019/10,096, 20%) that could lead to infection of more people with the virus. Other tweets discussed general knowledge and information (911/10,096, 9%) about the virus as well as concerns about the health care systems and workers (909/10,096, 9%). The remaining tweets discussed information about symptoms associated with COVID-19 (810/10,096, 8%), immunity (707/10,096, 7%), testing (605/10,096, 6%), and virus infection and transmission (503/10,096, 5%). CONCLUSIONS: Our findings indicate that Twitter and social media platforms can help identify important and useful knowledge shared by medical professionals during a pandemic. |*Attitude of Health Personnel[MESH] |*Social Media[MESH] |COVID-19[MESH] |Coronavirus Infections/epidemiology/*prevention & control[MESH] |Data Mining[MESH] |Humans[MESH] |Pandemics/*prevention & control[MESH] |Physicians/*psychology[MESH] |Pneumonia, Viral/epidemiology/*prevention & control[MESH]Mining Physicians Opinions on Social Media to Obtain Insights Into CO(epmc).pdf DeepDyve Pubget Overpricing