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10.2196/21933 http://scihub22266oqcxt.onion/10.2196/21933 33112757!7690969!33112757     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Internet+Res 2020 ; 22 (11): e21933 Nephropedia Template TP {{tp|p=33112757|t=2020. Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study |pdf=|usr=}}{{33112757}} gab.com Text Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study JO: J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=33112757 #FOAvip BACKGROUND: Various online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people's physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the epidemic may help generate useful strategies for guiding public emotions and dispelling rumors. OBJECTIVE: This study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19. METHODS: We used the web-crawling tool Scrapy to gather data published by People's Daily on Sina Weibo, a popular social media platform in China, after January 8, 2020. Netizens' comments under each Weibo post were collected. Nearly 1 million comments thus collected were divided into 5 categories: happiness, sadness, anger, fear, and neutral, based on the underlying emotional information identified and extracted from the comments by using a manual identification process. Data on rumors spread online were collected through Tencent's Jiaozhen platform. Time-lagged cross-correlation analyses were performed to examine the relationship between public emotions and rumors. RESULTS: Our results indicated that the angrier the public felt, the more rumors there would likely be (r=0.48, P<.001). Similar results were observed for the relationship between fear and rumors (r=0.51, P<.001) and between sadness and rumors (r=0.47, P<.001). Furthermore, we found a positive correlation between happiness and rumors, with happiness lagging the emergence of rumors by 1 day (r=0.56, P<.001). In addition, our data showed a significant positive correlation between fear and fearful rumors (r=0.34, P=.02). CONCLUSIONS: Our findings confirm that public emotions are related to the rumors spread online in the context of COVID-19 in China. Moreover, these findings provide several suggestions, such as the use of web-based monitoring methods, for relevant authorities and policy makers to guide public emotions and behavior during this public health emergency. Twit Text FOAVip Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study ????J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=33112757 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33112757 #FOAvip English Wikipedia <ref>{{Cite pmid|33112757}}</ref> Public Emotions and Rumors Spread During the COVID-19 Epidemic in China: Web-Based Correlation Study #MMPMID33112757 Dong W; Tao J; Xia X; Ye L; Xu H; Jiang P; Liu Y J Med Internet Res 2020[Nov]; 22 (11): e21933 PMID33112757show ga BACKGROUND: Various online rumors have led to inappropriate behaviors among the public in response to the COVID-19 epidemic in China. These rumors adversely affect people's physical and mental health. Therefore, a better understanding of the relationship between public emotions and rumors during the epidemic may help generate useful strategies for guiding public emotions and dispelling rumors. OBJECTIVE: This study aimed to explore whether public emotions are related to the dissemination of online rumors in the context of COVID-19. METHODS: We used the web-crawling tool Scrapy to gather data published by People's Daily on Sina Weibo, a popular social media platform in China, after January 8, 2020. Netizens' comments under each Weibo post were collected. Nearly 1 million comments thus collected were divided into 5 categories: happiness, sadness, anger, fear, and neutral, based on the underlying emotional information identified and extracted from the comments by using a manual identification process. Data on rumors spread online were collected through Tencent's Jiaozhen platform. Time-lagged cross-correlation analyses were performed to examine the relationship between public emotions and rumors. RESULTS: Our results indicated that the angrier the public felt, the more rumors there would likely be (r=0.48, P<.001). Similar results were observed for the relationship between fear and rumors (r=0.51, P<.001) and between sadness and rumors (r=0.47, P<.001). Furthermore, we found a positive correlation between happiness and rumors, with happiness lagging the emergence of rumors by 1 day (r=0.56, P<.001). In addition, our data showed a significant positive correlation between fear and fearful rumors (r=0.34, P=.02). CONCLUSIONS: Our findings confirm that public emotions are related to the rumors spread online in the context of COVID-19 in China. Moreover, these findings provide several suggestions, such as the use of web-based monitoring methods, for relevant authorities and policy makers to guide public emotions and behavior during this public health emergency. |COVID-19/*epidemiology/*psychology[MESH] |China/epidemiology[MESH] |Correlation of Data[MESH] |Emotions/*physiology[MESH] |Female[MESH] |Humans[MESH] |Internet[MESH] |Male[MESH] |Pandemics[MESH]Public Emotions and Rumors Spread During the COVID-19 Epidemic in Chin(epmc).pdf DeepDyve Pubget Overpricing