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10.1007/s10489-020-02029-z http://scihub22266oqcxt.onion/10.1007/s10489-020-02029-z C7646503!7646503!34764561     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Appl+Intell+(Dordr) 2021 ; 51 (5): 2790-804 Nephropedia Template TP {{tp|p=34764561|t=2021. Design and analysis of a large-scale COVID-19 tweets dataset |pdf=|usr=}}{{34764561}} gab.com Text Design and analysis of a large-scale COVID-19 tweets dataset JO: Appl Intell (Dordr) http://www.kidney.de/pget.php?&tw=1&pmid=34764561 #FOAvip As of July 17, 2020, more than thirteen million people have been diagnosed with the Novel Coronavirus (COVID-19), and half a million people have already lost their lives due to this infectious disease. The World Health Organization declared the COVID-19 outbreak as a pandemic on March 11, 2020. Since then, social media platforms have experienced an exponential rise in the content related to the pandemic. In the past, Twitter data have been observed to be indispensable in the extraction of situational awareness information relating to any crisis. This paper presents COV19Tweets Dataset (Lamsal 2020a), a large-scale Twitter dataset with more than 310 million COVID-19 specific English language tweets and their sentiment scores. The dataset?s geo version, the GeoCOV19Tweets Dataset (Lamsal 2020b), is also presented. The paper discusses the datasets? design in detail, and the tweets in both the datasets are analyzed. The datasets are released publicly, anticipating that they would contribute to a better understanding of spatial and temporal dimensions of the public discourse related to the ongoing pandemic. As per the stats, the datasets (Lamsal 2020a, 2020b) have been accessed over 74.5k times, collectively. Twit Text FOAVip Design and analysis of a large-scale COVID-19 tweets dataset ????Appl Intell (Dordr) http://www.kidney.de/pget.php?&tw=1&pmid=34764561 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34764561 #FOAvip English Wikipedia <ref>{{Cite pmid|34764561}}</ref> Design and analysis of a large-scale COVID-19 tweets dataset #MMPMID34764561 Lamsal R Appl Intell (Dordr) 2021[]; 51 (5): 2790-804 PMID34764561show ga As of July 17, 2020, more than thirteen million people have been diagnosed with the Novel Coronavirus (COVID-19), and half a million people have already lost their lives due to this infectious disease. The World Health Organization declared the COVID-19 outbreak as a pandemic on March 11, 2020. Since then, social media platforms have experienced an exponential rise in the content related to the pandemic. In the past, Twitter data have been observed to be indispensable in the extraction of situational awareness information relating to any crisis. This paper presents COV19Tweets Dataset (Lamsal 2020a), a large-scale Twitter dataset with more than 310 million COVID-19 specific English language tweets and their sentiment scores. The dataset?s geo version, the GeoCOV19Tweets Dataset (Lamsal 2020b), is also presented. The paper discusses the datasets? design in detail, and the tweets in both the datasets are analyzed. The datasets are released publicly, anticipating that they would contribute to a better understanding of spatial and temporal dimensions of the public discourse related to the ongoing pandemic. As per the stats, the datasets (Lamsal 2020a, 2020b) have been accessed over 74.5k times, collectively. äDesign and analysis of a large-scale COVID-19 tweets dataset (epmc).pdf DeepDyve Pubget Overpricing