Research on Information Visualization Design for Reducing Cognitive Anxiety during the Epidemic
DOI:
https://doi.org/10.54691/bcpssh.v14i.163Keywords:
New Crown Pneumonia Epidemic; Reduce Cognitive Anxiety; Information Visualization.Abstract
Purpose: To reduce people’s cognitive anxiety during the special period of the epidemic through the use of information visualization methods, and to build a psychological construction for correct understanding of the epidemic. Methods: Analyze the causes of cognitive anxiety, and propose to reduce cognitive anxiety through data screening and display and visualization design in information visualization design, to reduce people’s cognitive anxiety in emergencies. Conclusion: Through the design of the new coronary pneumonia epidemic data visualization network platform, it provides a valuable model for the research on how to reduce cognitive anxiety through information visualization design.
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References
Qiu Dehui. Mathematical Emotions[M]. Beijing: CPC Central Party School Press. 2018.
You Wubing. The Care Ethics Adjustment Of "Epidemic Anxiety"[N]. Journal of Wuhan University of Science and Technology. 2020(8): 370-375.
Fu Xinyi, Liu Shixia, Xu Yingqing. The Development and Reflection of Information Visualization[J]. Art & Design. 2017(4): 16-19.
Jiang Sujia. Infodemic: Study on the Spread of Response to Rumors about COVID-19[J]. Studies on Science Popularization. 2020(2): 72-78.
Sun Manqin, Li Shanshan, Yue Hongyu, et al. Analysis on Anxiety Status of Chinese Netizens under the Outbreak of the Coronavirus Disease 2019(COVID-19) and Its Influencing Factors[J]. Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology. 2020(4): 686- 691.
Li Tuo. Information Visualization: A Design Method of Making the Epidemic 'Visible' to the Public[J]. Art & Design. 2020(2): 38-45.
Yin Lingling, Feng Mei, Zhang Hui, et al. Influence of Different Colors of Nurses' Uniform on the Anxiety Level of Hospitalized Children[J]. Chinese Nursing Research. 2010(8): 2119-2120.
Ai Min, Liu Yuhong, Qi Xiaohong, et al. e Impact of Color on Human Physiology and Psychology[J]. China Journal of Health Psychology. 2015:317-320.
Yiting Wang, Ting Wang, Ying Cui, Honghui Mei, et al. COVID-19 Data Visualization Public Welfare Activity [J]. Visual Informatics.2020:51-54.
Qin Jingyan, Zhu Xiangwei, Li Danbilin. Preliminary Study of the Interactive Design Method in Visualized Information [J]. Digital Art Forum. 2007(8): 22-23.
Jeeyun Oh, Hayoung Sally Lim, Jacob G. Copplea, Emily. Chadraba. Harnessing The Persuasive Potential of Data: The Combinatory Effects of Data Visualization and Interactive Narratives on Obesity Perceptions and Policy Attitudes [J]. Telematics and Informatics. 20018(8):1755-1769.
Mike K.P. Soa, Agnes Tiwarib, Amanda M.Y. Chud, Jenny T.Y. Tsangd, Jacky N.L. Chan. Visualizing COVID-19 Pandemic Risk Through Network Connectedness [J]. International Journal of Infectious Diseases. 2020:558-561.
Arran Hamlet a, Kévin Jean a, Sergio Yactayo, et al. POLICI: A Web Application for Visualizing and Extracting Yellow Fever Vaccination Coverage in Africa[J]. Vaccine.2019:1384–1388.
Laszlo Robert Kolozsvari, Tamas Berczes, Andras Hajdu et al. Al-Tammemi, Gergo Jozsef Szollosi, Szilvia Harsanyi, Szabolcs Garboczy, Judit Zsuga. Predicting the Epidemic Curve of the Coronavirus (SARS-CoV-2) Disease (COVID-19) Using Artificial Intelligence: An Application on the First and Second Waves[J]. Informatics in Medicine Unlocked.2021.
Feng Chen, Shi Zhang. Information Visualization Analysis of Public Opinion Data on social media[J]. Informatica.2021:157-162.
Madeleine Sorapure. Text, Image, Data, Interaction: Understanding Information Visualization[J]. Computers and Composition.2019.
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