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10.1016/j.puhe.2021.08.019 http://scihub22266oqcxt.onion/10.1016/j.puhe.2021.08.019 34628307!8494632!34628307     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Public+Health 2021 ; 200 (ä): 4-6 Nephropedia Template TP {{tp|p=34628307|t=2021. An analysis of AstraZeneca COVID-19 vaccine misinformation and fear mongering on Twitter |pdf=|usr=}}{{34628307}} gab.com Text An analysis of AstraZeneca COVID-19 vaccine misinformation and fear mongering on Twitter JO: Public Health http://www.kidney.de/pget.php?&tw=1&pmid=34628307 #FOAvip OBJECTIVES: The objective of this study was to analyse the media discourse about the AstraZeneca COVID-19 vaccine on Twitter. STUDY DESIGN: The study design used in this study is data scraping, media analysis, social network analysis, and botometer. METHODS: We collected 221,922 tweets containing '#AstraZeneca' from 1 January 2021 to 22 March 2021. From 50,080 tweets in the English language, we analysed the linked media sources and conducted a network detection study. RESULTS: We found that the most frequently retweeted tweets were full of negative information, and in many cases came from media sources that are well-known for misinformation. Our analysis identified large coordination networks involved in political astroturfing and vaccine diplomacy in South Asia but also vaccine advocacy networks associated with European Commission employees. CONCLUSIONS: The results of this study show that Twitter discourse about #AstraZeneca is filled with misinformation and bad press, and may be distributed not only organically by anti-vaxxer activists but also systematically by professional sources. Twit Text FOAVip An analysis of AstraZeneca COVID-19 vaccine misinformation and fear mongering on Twitter ????Public Health http://www.kidney.de/pget.php?&tw=1&pmid=34628307 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34628307 #FOAvip English Wikipedia <ref>{{Cite pmid|34628307}}</ref> An analysis of AstraZeneca COVID-19 vaccine misinformation and fear mongering on Twitter #MMPMID34628307 Jemielniak D; Krempovych Y Public Health 2021[Nov]; 200 (ä): 4-6 PMID34628307show ga OBJECTIVES: The objective of this study was to analyse the media discourse about the AstraZeneca COVID-19 vaccine on Twitter. STUDY DESIGN: The study design used in this study is data scraping, media analysis, social network analysis, and botometer. METHODS: We collected 221,922 tweets containing '#AstraZeneca' from 1 January 2021 to 22 March 2021. From 50,080 tweets in the English language, we analysed the linked media sources and conducted a network detection study. RESULTS: We found that the most frequently retweeted tweets were full of negative information, and in many cases came from media sources that are well-known for misinformation. Our analysis identified large coordination networks involved in political astroturfing and vaccine diplomacy in South Asia but also vaccine advocacy networks associated with European Commission employees. CONCLUSIONS: The results of this study show that Twitter discourse about #AstraZeneca is filled with misinformation and bad press, and may be distributed not only organically by anti-vaxxer activists but also systematically by professional sources. |*COVID-19[MESH] |*Social Media[MESH] |COVID-19 Vaccines[MESH] |Communication[MESH] |Fear[MESH] |Humans[MESH]An analysis of AstraZeneca COVID-19 vaccine misinformation and fear mo(epmc).pdf DeepDyve Pubget Overpricing