Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1089/cyber.2020.0425 http://scihub22266oqcxt.onion/10.1089/cyber.2020.0425 32813572!ä!32813572 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 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Cyberpsychol+Behav+Soc+Netw 2020 ; 23 (12): 889-893 Nephropedia Template TP {{tp|p=32813572|t=2020. A Content Analysis of Coronavirus Tweets in the United States Just Prior to the Pandemic Declaration |pdf=|usr=}}{{32813572}} gab.com Text A Content Analysis of Coronavirus Tweets in the United States Just Prior to the Pandemic Declaration JO: Cyberpsychol Behav Soc Netw http://www.kidney.de/pget.php?&tw=1&pmid=32813572 #FOAvip This study examined public comments on Twitter about coronavirus in the weeks after news stories across the globe on the coronavirus outbreak. A total of 600 tweets were assessed (N = 600) for sentiment, risks presented, attribution of blame, and outrage. A sample of 300 tweets was taken from Sunday, February 9, through Wednesday, February 19, 2020, and an additional 300 tweets from Sunday, March 1, through Wednesday, March 11, 2020, to assess how public communication changed over time. Results show that risk, blame, and outrage differed significantly between February and March in a variety of ways. Specifically, more significant risks were noted in February than in March, with the majority of March tweets not noting any specific risks. Although most tweets did not present any specific blame, more blame was presented in February than in March, although more tweets in March attributed blame to countries and governments. Finally, outrage varied in several ways, with hazards generally being higher in February and outrage being higher in March. Twit Text FOAVip A Content Analysis of Coronavirus Tweets in the United States Just Prior to the Pandemic Declaration ????Cyberpsychol Behav Soc Netw http://www.kidney.de/pget.php?&tw=1&pmid=32813572 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32813572 #FOAvip English Wikipedia <ref>{{Cite pmid|32813572}}</ref> A Content Analysis of Coronavirus Tweets in the United States Just Prior to the Pandemic Declaration #MMPMID32813572 Damiano AD; Allen Catellier JR Cyberpsychol Behav Soc Netw 2020[Dec]; 23 (12): 889-893 PMID32813572show ga This study examined public comments on Twitter about coronavirus in the weeks after news stories across the globe on the coronavirus outbreak. A total of 600 tweets were assessed (N = 600) for sentiment, risks presented, attribution of blame, and outrage. A sample of 300 tweets was taken from Sunday, February 9, through Wednesday, February 19, 2020, and an additional 300 tweets from Sunday, March 1, through Wednesday, March 11, 2020, to assess how public communication changed over time. Results show that risk, blame, and outrage differed significantly between February and March in a variety of ways. Specifically, more significant risks were noted in February than in March, with the majority of March tweets not noting any specific risks. Although most tweets did not present any specific blame, more blame was presented in February than in March, although more tweets in March attributed blame to countries and governments. Finally, outrage varied in several ways, with hazards generally being higher in February and outrage being higher in March. |*COVID-19[MESH] |*Disease Outbreaks[MESH] |Communication[MESH] |Consumer Health Information/*trends[MESH] |Humans[MESH] |SARS-CoV-2[MESH] |Social Media/*trends[MESH]A Content Analysis of Coronavirus Tweets in the United States Just Pri(epmc).pdf DeepDyve Pubget Overpricing