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10.1080/10810730.2021.1955050 http://scihub22266oqcxt.onion/10.1080/10810730.2021.1955050 34346288!ä!34346288 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Health+Commun 2021 ; 26 (7): 443-459 Nephropedia Template TP {{tp|p=34346288|t=2021. COVID-19 Vaccine Discourse on Twitter: A Content Analysis of Persuasion Techniques, Sentiment and Mis/Disinformation |pdf=|usr=}}{{34346288}} gab.com Text COVID-19 Vaccine Discourse on Twitter: A Content Analysis of Persuasion Techniques, Sentiment and Mis/Disinformation JO: J Health Commun http://www.kidney.de/pget.php?&tw=1&pmid=34346288 #FOAvip This research aims to understand the persuasion techniques used in Twitter posts about COVID-19 vaccines by the different vaccine sentiments (i.e., Pro-Vaccine, Anti-Vaccine, and Neutral) using the Elaboration Likelihood Model, Social judgment Theory, and the Extended Parallel Process Model as theoretical frameworks. A content analysis was conducted on a data set of 1,000 Twitter posts. The corpus of Tweets was examined using the persuasion frameworks; tweets that were identified as emanating from bots were further examined. Results found Anti-Vaccine messages predominantly used Anecdotal stories, Humor/Sarcasm, and Celebrity figures as persuasion techniques, while Pro-Vaccine messages primarily used Information, Celebrity figures, and Participation. Results also showed the Anti-Vaccine messages primarily focused on values related to the categories of Safety, Political/Conspiracy Theories, and Choice. Finally, results revealed Anti-Vaccine messages primarily used Perceived Severity and Perceived Susceptibility, which are fear appeal elements. The findings for messages by bots were comparable to the messages in the larger corpus of tweets. Based on the findings, a response framework-Health Information Persuasion Exploration (HIPE)-is proposed to address mis/disinformation and Anti-Vaccine messaging. The results of this study and the HIPE framework can inform a national COVID-19 vaccine health campaign to increase vaccine adoption. Twit Text FOAVip COVID-19 Vaccine Discourse on Twitter: A Content Analysis of Persuasion Techniques, Sentiment and Mis/Disinformation ????J Health Commun http://www.kidney.de/pget.php?&tw=1&pmid=34346288 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34346288 #FOAvip English Wikipedia <ref>{{Cite pmid|34346288}}</ref> COVID-19 Vaccine Discourse on Twitter: A Content Analysis of Persuasion Techniques, Sentiment and Mis/Disinformation #MMPMID34346288 Scannell D; Desens L; Guadagno M; Tra Y; Acker E; Sheridan K; Rosner M; Mathieu J; Fulk M J Health Commun 2021[Jul]; 26 (7): 443-459 PMID34346288show ga This research aims to understand the persuasion techniques used in Twitter posts about COVID-19 vaccines by the different vaccine sentiments (i.e., Pro-Vaccine, Anti-Vaccine, and Neutral) using the Elaboration Likelihood Model, Social judgment Theory, and the Extended Parallel Process Model as theoretical frameworks. A content analysis was conducted on a data set of 1,000 Twitter posts. The corpus of Tweets was examined using the persuasion frameworks; tweets that were identified as emanating from bots were further examined. Results found Anti-Vaccine messages predominantly used Anecdotal stories, Humor/Sarcasm, and Celebrity figures as persuasion techniques, while Pro-Vaccine messages primarily used Information, Celebrity figures, and Participation. Results also showed the Anti-Vaccine messages primarily focused on values related to the categories of Safety, Political/Conspiracy Theories, and Choice. Finally, results revealed Anti-Vaccine messages primarily used Perceived Severity and Perceived Susceptibility, which are fear appeal elements. The findings for messages by bots were comparable to the messages in the larger corpus of tweets. Based on the findings, a response framework-Health Information Persuasion Exploration (HIPE)-is proposed to address mis/disinformation and Anti-Vaccine messaging. The results of this study and the HIPE framework can inform a national COVID-19 vaccine health campaign to increase vaccine adoption. |*COVID-19 Vaccines[MESH] |*Communication[MESH] |Anti-Vaccination Movement[MESH] |COVID-19/epidemiology/prevention & control[MESH] |Humans[MESH] |Persuasive Communication[MESH] |Social Media/*statistics & numerical data[MESH]COVID-19 Vaccine Discourse on Twitter: A Content Analysis of Persuasio(epmc).pdf DeepDyve Pubget Overpricing