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10.1007/s00168-022-01133-x http://scihub22266oqcxt.onion/10.1007/s00168-022-01133-x 35602240!9110940!35602240     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       Ann+Reg+Sci 2022 ; ä (ä): 1-20 Nephropedia Template TP {{tp|p=35602240|t=2022. Online citizen petitions related to COVID-19 in South Korean cities: a big data analysis |pdf=|usr=}}{{35602240}} gab.com Text Online citizen petitions related to COVID-19 in South Korean cities: a big data analysis JO: Ann Reg Sci http://www.kidney.de/pget.php?&tw=1&pmid=35602240 #FOAvip What do citizens demand of their governing bodies to cope with the spread of emerging infectious diseases after recognizing the growing danger? What are the similarities and differences in political participation via online citizen petitions regarding COVID-19 across cities with different degrees of pandemic experience? This study aims to answer these questions by examining citizen petitions regarding the COVID-19 pandemic in urban areas of South Korea. The pattern of citizens' requests is a part of integrative socio-ecological and political systems with spatial and temporal dimensions. We compare the pattern of online citizen petitions in four Korean cities, namely Seoul, Busan, Daegu, and Incheon, some of which were epicenters of the COVID-19 outbreak. By applying relevant big data analysis techniques such as text mining, topic modeling, and network analysis, we compare the characteristics of citizen petitions on COVID-19 in the four cities, particularly whether (and how) they want financial or welfare support or COVID-19 prevention. We find that cities that experience a rapid spread are likely to have more petitions for prevention than for support. By comparison, cities without such experience are likely to have more petitions for support. This study contributes by tracing citizen and local government interactions in response to emerging infectious diseases by empirically analyzing the related big data on petitions. Policy implications suggest that urban authorities should listen to analyze and respond to the urgent needs of citizens. Twit Text FOAVip Online citizen petitions related to COVID-19 in South Korean cities: a big data analysis ????Ann Reg Sci http://www.kidney.de/pget.php?&tw=1&pmid=35602240 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35602240 #FOAvip English Wikipedia <ref>{{Cite pmid|35602240}}</ref> Online citizen petitions related to COVID-19 in South Korean cities: a big data analysis #MMPMID35602240 Lee T; Paik W; Lim S; Lee SY Ann Reg Sci 2022[May]; ä (ä): 1-20 PMID35602240show ga What do citizens demand of their governing bodies to cope with the spread of emerging infectious diseases after recognizing the growing danger? What are the similarities and differences in political participation via online citizen petitions regarding COVID-19 across cities with different degrees of pandemic experience? This study aims to answer these questions by examining citizen petitions regarding the COVID-19 pandemic in urban areas of South Korea. The pattern of citizens' requests is a part of integrative socio-ecological and political systems with spatial and temporal dimensions. We compare the pattern of online citizen petitions in four Korean cities, namely Seoul, Busan, Daegu, and Incheon, some of which were epicenters of the COVID-19 outbreak. By applying relevant big data analysis techniques such as text mining, topic modeling, and network analysis, we compare the characteristics of citizen petitions on COVID-19 in the four cities, particularly whether (and how) they want financial or welfare support or COVID-19 prevention. We find that cities that experience a rapid spread are likely to have more petitions for prevention than for support. By comparison, cities without such experience are likely to have more petitions for support. This study contributes by tracing citizen and local government interactions in response to emerging infectious diseases by empirically analyzing the related big data on petitions. Policy implications suggest that urban authorities should listen to analyze and respond to the urgent needs of citizens. äOnline citizen petitions related to COVID-19 in South Korean cities: a(epmc).pdf DeepDyve Pubget Overpricing