Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics. (November 2020)
- Record Type:
- Journal Article
- Title:
- Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics. (November 2020)
- Main Title:
- Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics
- Authors:
- Zhu, Bangren
Zheng, Xinqi
Liu, Haiyan
Li, Jiayang
Wang, Peipei - Abstract:
- Highlights: Discover the new characteristics of the "double peaks" of public opinion. Popular topics have the characteristic of slowly declining over time. There is no inevitable temporal and spatial consistency between topics of high concern and topics of low emotion. Abstract: COVID-19 blocked Wuhan in China, which was sealed off on Chinese New Year's Eve. During this period, the research on the relevant topics of COVID-19 and emotional expressions published on social media can provide decision support for the management and control of large-scale public health events. The research assisted the analysis of microblog text topics with the help of the LDA model, and obtained 8 topics ("origin", "host", "organization", "quarantine measures", "role models", "education", "economic", "rumor") and 28 interactive topics. Obtain data through crawler tools, with the help of big data technology, social media topics and emotional change characteristics are analyzed from spatiotemporal perspectives. The results show that: (1) "Double peaks" feature appears in the epidemic topic search curve. Weibo on the topic of the epidemic gradually reduced after January 24. However, the proportion of epidemic topic searches has gradually increased, and a "double peaks" phenomenon appeared within a week; (2) The topic changes with time and the fluctuation of the topic discussion rate gradually weakens. The number of texts on different topics and interactive topics changes with time. At the same time,Highlights: Discover the new characteristics of the "double peaks" of public opinion. Popular topics have the characteristic of slowly declining over time. There is no inevitable temporal and spatial consistency between topics of high concern and topics of low emotion. Abstract: COVID-19 blocked Wuhan in China, which was sealed off on Chinese New Year's Eve. During this period, the research on the relevant topics of COVID-19 and emotional expressions published on social media can provide decision support for the management and control of large-scale public health events. The research assisted the analysis of microblog text topics with the help of the LDA model, and obtained 8 topics ("origin", "host", "organization", "quarantine measures", "role models", "education", "economic", "rumor") and 28 interactive topics. Obtain data through crawler tools, with the help of big data technology, social media topics and emotional change characteristics are analyzed from spatiotemporal perspectives. The results show that: (1) "Double peaks" feature appears in the epidemic topic search curve. Weibo on the topic of the epidemic gradually reduced after January 24. However, the proportion of epidemic topic searches has gradually increased, and a "double peaks" phenomenon appeared within a week; (2) The topic changes with time and the fluctuation of the topic discussion rate gradually weakens. The number of texts on different topics and interactive topics changes with time. At the same time, the discussion rate of epidemic topics gradually weakens; (3) The political and economic center is an area where social media is highly concerned. The areas formed by Beijing, Shanghai, Guangdong, Sichuan and Hubei have published more microblog texts. The spatial division of the number of Weibo social media texts has a high correlation with the economic zone division; (4) The existence of the topic of "rumor" will enable people to have more communication and discussion. The interactive topics of "rumors" always have higher topic popularity and low emotion text expressions. Through the analysis of media information, it helps relevant decision makers to grasp social media topics from spatiotemporal characteristics, so that relevant departments can accurately grasp the public's subjective ideas and emotional expressions, and provide decision support for macro-control response strategies and measures and risk communication. … (more)
- Is Part Of:
- Chaos, solitons and fractals. Volume 140(2020)
- Journal:
- Chaos, solitons and fractals
- Issue:
- Volume 140(2020)
- Issue Display:
- Volume 140, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 140
- Issue:
- 2020
- Issue Sort Value:
- 2020-0140-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11
- Subjects:
- COVID-19 -- Epidemic topics -- Social media -- Spatiotemporal characteristics
Chaotic behavior in systems -- Periodicals
Solitons -- Periodicals
Fractals -- Periodicals
Chaotic behavior in systems
Fractals
Solitons
Periodicals
003.7 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/09600779 ↗ - DOI:
- 10.1016/j.chaos.2020.110123 ↗
- Languages:
- English
- ISSNs:
- 0960-0779
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3129.716000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14938.xml