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10.3390/vaccines9050421 http://scihub22266oqcxt.onion/10.3390/vaccines9050421 33922343!8146829!33922343     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Vaccines+(Basel) 2021 ; 9 (5): ä Nephropedia Template TP {{tp|p=33922343|t=2021. #Scamdemic, #Plandemic, or #Scaredemic: What Parler Social Media Platform Tells Us about COVID-19 Vaccine |pdf=|usr=}}{{33922343}} gab.com Text #Scamdemic, #Plandemic, or #Scaredemic: What Parler Social Media Platform Tells Us about COVID-19 Vaccine JO: Vaccines (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=33922343 #FOAvip This study aims to understand public discussions regarding COVID-19 vaccine on Parler, a newer social media platform that recently gained in popularity. Through analyzing a random sample (n = 400) of Parler posts using the hashtags #COVID19Vaccine and #NoCovidVaccine, we use the concept of echo chambers to understand users' discussions through a text analytics approach. Thematic analysis reveals five key themes: reasons to refuse the COVID-19 vaccine (40%), side effects of the COVID-19 vaccine (28%), population control through the COVID-19 vaccine (23%), children getting vaccinated without parental consent (5%), and comparison of other health issues with COVID-19 (2%). Textual analysis shows that the most frequently used words in the corpus were: nocovidvaccine (348); vaccine (264); covid (184); covid19 (157); and vaccines (128). These findings suggest that users adopted different terms and hashtags to express their beliefs regarding the COVID-19 vaccine. Further, findings revealed that users used certain hashtags such as "echo" to encourage like-minded people to reinforce their existing beliefs on COVID-19 vaccine efficacy and vaccine acceptance. These findings have implications for public health communication in attempts to correct false narratives on social media platforms. Through widely sharing the scientific findings of COVID-19 vaccine-related studies can help individuals understand the COVID-19 vaccines efficacy accurately. Twit Text FOAVip #Scamdemic, #Plandemic, or #Scaredemic: What Parler Social Media Platform Tells Us about COVID-19 Vaccine ????Vaccines (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=33922343 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33922343 #FOAvip English Wikipedia <ref>{{Cite pmid|33922343}}</ref> #Scamdemic, #Plandemic, or #Scaredemic: What Parler Social Media Platform Tells Us about COVID-19 Vaccine #MMPMID33922343 Baines A; Ittefaq M; Abwao M Vaccines (Basel) 2021[Apr]; 9 (5): ä PMID33922343show ga This study aims to understand public discussions regarding COVID-19 vaccine on Parler, a newer social media platform that recently gained in popularity. Through analyzing a random sample (n = 400) of Parler posts using the hashtags #COVID19Vaccine and #NoCovidVaccine, we use the concept of echo chambers to understand users' discussions through a text analytics approach. Thematic analysis reveals five key themes: reasons to refuse the COVID-19 vaccine (40%), side effects of the COVID-19 vaccine (28%), population control through the COVID-19 vaccine (23%), children getting vaccinated without parental consent (5%), and comparison of other health issues with COVID-19 (2%). Textual analysis shows that the most frequently used words in the corpus were: nocovidvaccine (348); vaccine (264); covid (184); covid19 (157); and vaccines (128). These findings suggest that users adopted different terms and hashtags to express their beliefs regarding the COVID-19 vaccine. Further, findings revealed that users used certain hashtags such as "echo" to encourage like-minded people to reinforce their existing beliefs on COVID-19 vaccine efficacy and vaccine acceptance. These findings have implications for public health communication in attempts to correct false narratives on social media platforms. Through widely sharing the scientific findings of COVID-19 vaccine-related studies can help individuals understand the COVID-19 vaccines efficacy accurately. ä#Scamdemic, #Plandemic, or #Scaredemic: What Parler Social Media Platf(epmc).pdf DeepDyve Pubget Overpricing