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.

10.3233/SHTI210084 http://scihub22266oqcxt.onion/10.3233/SHTI210084 33965914!ä!33965914 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Stud+Health+Technol+Inform 2021 ; 279 (ä): 26-33 Nephropedia Template TP {{tp|p=33965914|t=2021. Topic Discovery on Farsi, English, French, and Arabic Tweets Related to COVID-19 Using Text Mining Techniques |pdf=|usr=}}{{33965914}} gab.com Text Topic Discovery on Farsi, English, French, and Arabic Tweets Related to COVID-19 Using Text Mining Techniques JO: Stud Health Technol Inform http://www.kidney.de/pget.php?&tw=1&pmid=33965914 #FOAvip BACKGROUND: Social networks are a good source for monitoring public health during the outbreak of COVID-19, these networks play an important role in identifying useful information. OBJECTIVES: This study aims to draw a comparison of the public's reaction in Twitter among the countries of West Asia (a.k.a Middle East) and North Africa in order to make an understanding of their response regarding the same global threat. METHODS: 766,630 tweets in four languages (Arabic, English French, and Farsi) tweeted in March 2020, were investigated. RESULTS: The results indicate that the only common theme among all languages is "government responsibilities (political)" which indicates the importance of this subject for all nations. CONCLUSION: Although nations react similarly in some aspects, they respond differently in others and therefore, policy localization is a vital step in confronting problems such as COVID-19 pandemic. Twit Text FOAVip Topic Discovery on Farsi, English, French, and Arabic Tweets Related to COVID-19 Using Text Mining Techniques ????Stud Health Technol Inform http://www.kidney.de/pget.php?&tw=1&pmid=33965914 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33965914 #FOAvip English Wikipedia <ref>{{Cite pmid|33965914}}</ref> Topic Discovery on Farsi, English, French, and Arabic Tweets Related to COVID-19 Using Text Mining Techniques #MMPMID33965914 Jafarian H; Mohammadi M; Javaheri A; Sukarieh M; Yoosefi Nejad M; Sheikhtaheri A; Hosseinzadeh M; Momeni-Ortner E; Rawassizadeh R Stud Health Technol Inform 2021[May]; 279 (ä): 26-33 PMID33965914show ga BACKGROUND: Social networks are a good source for monitoring public health during the outbreak of COVID-19, these networks play an important role in identifying useful information. OBJECTIVES: This study aims to draw a comparison of the public's reaction in Twitter among the countries of West Asia (a.k.a Middle East) and North Africa in order to make an understanding of their response regarding the same global threat. METHODS: 766,630 tweets in four languages (Arabic, English French, and Farsi) tweeted in March 2020, were investigated. RESULTS: The results indicate that the only common theme among all languages is "government responsibilities (political)" which indicates the importance of this subject for all nations. CONCLUSION: Although nations react similarly in some aspects, they respond differently in others and therefore, policy localization is a vital step in confronting problems such as COVID-19 pandemic. |*COVID-19[MESH] |*Social Media[MESH] |Asia[MESH] |Data Mining[MESH] |Humans[MESH] |Language[MESH] |Middle East[MESH] |Pandemics[MESH]Topic Discovery on Farsi, English, French, and Arabic Tweets Related t(epmc).pdf DeepDyve Pubget Overpricing