Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-11-28 Cooperative journals: 《数据智能（英文）》
Abstract： Since the end of 2019, the COVID-19 outbreak worldwide has not only presented challenges for government agencies in addressing public health emergency, but also tested their capacity in dealing with public opinion on social media and responding to social emergencies. To understand the impact of COVID- 19 related tweets posted by the major public health agencies in the United States on public emotion, this paper studied public emotional diffusion in the tweets network, including its process and characteristics, by taking Twitter users of four official public health systems in the United States as an example. We extracted the interactions between tweets in the COVID-19-TweetIds data set and drew the tweets diffusion network. We proposed a method to measure the characteristics of the emotional diffusion network, with which we analyzed the changes of the public emotional intensity and the proportion of emotional polarity, investigated the emotional influence of key nodes and users, and the emotional diffusion of tweets at different tweeting time, tweet topics and the tweet posting agencies. The results show that the emotional polarity of tweets has changed from negative to positive with the improvement of pandemic management measures. The public's emotional polarity on pandemic related topics tends to be negative, and the emotional intensity of management measures such as pandemic medical services turn from positive to negative to the greatest extent, while the emotional intensity of pandemic related knowledge changes the most. The tweets posted by the Centers for Disease Control and Prevention and the Food and Drug Administration of the United States have a broad impact on public emotions, and the emotional spread of tweets’ polarity eventually forms a very close proportion of opposite emotions.
Subjects: Management Science >> Other Disciplines of Management Science submitted time 2022-11-24 Cooperative journals: 《2022年第三届传播、创新和经济管理国际研讨会》
Abstract： After the outbreak of the new crown epidemic in 2020, the national economy has entered a deeper digital era. The rise of community group buying not only avoids the gathering of people buying daily necessities, but also wins the favor of the people with lower prices. Since 2020, internet companies such as Meituan, Didi Chuxing, and Pin duoduo have joined the community group buying industry one after another, hoping to make a big splash in the fresh food e-commerce field through community group buying. important strategic deployment. This paper makes suggestions on how community group buying can deepen the sink market and promote the country's economic development, from the competitive advantages of the sink market, the current state of cold chain e-commerce development in the sink market, and the problems that exist, to multiple dimensions of future development.
Subjects: Mathematics >> Applied Mathematics submitted time 2021-09-22
Abstract： In the early days of the epidemic of coronavirus disease 2019 (COVID-19), due to insufficient knowledge of the pandemic, inadequate nucleic acid tests, lack of timely data reporting, etc., the origin time of the onset of COVID-19 is difficult to determine. Therefore, source tracing is crucial for infectious disease prevention and control. The purpose of this paper is to infer the origin time of pandemic of COVID-19 based on a data and model hybrid driven method. We model the testing positive rate to fit its actual trend, and use the least squares estimation to obtain the optimal model parameters. Further, the kernel density estimation is applied to infer the origin time of pandemic given the specific confidence probability. By selecting 12 representative regions in the United States for analysis, the dates of the first infected case with 50% confidence probability are mostly between August and October 2019, which are earlier than the officially announced date of the first confirmed case in the United States on January 20, 2020. The experimental results indicate that the COVID-19 pandemic in the United States starts to spread around September 2019 with a high confidence probability. In addition, the existing confirmed cases are also used in Wuhan City and Zhejiang Province in China to infer the origin time of COVID-19 and provide the confidence probability. The results show that the spread of COVID-19 pandemic in China is likely to begin in late December 2019. " " "
Peer Review Status:
Awaiting Review
Hits
Hits
Downloads
Comment