| Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis | |
Young, Sean D.1,2; Zhang, Qingpeng3; Zeng, Daniel Dajun4 ; Zhan, Yongcheng5; Cumberland, William6
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| Source Publication | JOURNAL OF MEDICAL INTERNET RESEARCH
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| ISSN | 1438-8871 |
| 2022-03-01 | |
| Volume | 24Issue:3Pages:5 |
| Corresponding Author | Young, Sean D.(syoung5@hs.uci.edu) |
| Abstract | Background: Innovative surveillance methods are needed to assess adherence to COVID-19 recommendations, especially methods that can provide near real-time or highly geographically targeted data. Use of location-based social media image data (eg, Instagram images) is one possible approach that could be explored to address this problem. Objective: We seek to evaluate whether publicly available near real-time social media images might be used to monitor COVID-19 health policy adherence. Methods: We collected a sample of 43,487 Instagram images in New York from February 7 to April 11, 2020, from the following location hashtags: #Centralpark (n=20,937), #Brooklyn Bridge (n=14,875), and #Timesquare (n=7675). After manually reviewing images for accuracy, we counted and recorded the frequency of valid daily posts at each of these hashtag locations over time, as well as rated and counted whether the individuals in the pictures at these location hashtags were social distancing (ie, whether the individuals in the images appeared to be distanced from others vs next to or touching each other). We analyzed the number of images posted over time and the correlation between trends among hashtag locations. Results: We found a statistically significant decline in the number of posts over time across all regions, with an approximate decline of 17% across each site (P<.001). We found a positive correlation between hashtags (#Centralpark and #Brooklynbridge: r=0.40; #BrooklynBridge and #Timesquare: r=0.41; and #Timesquare and #Centralpark: r=0.33; P<.001 for all correlations). The logistic regression analysis showed a mild statistically significant increase in the proportion of posts over time with people appearing to be social distancing at Central Park (P=.004) and Brooklyn Bridge (P=.02) but not for Times Square (P=.16). Conclusions: Results suggest the potential of using location-based social media image data as a method for surveillance of COVID-19 health policy adherence. Future studies should further explore the implementation and ethical issues associated with this approach. |
| Keyword | internet social media health informatics tool monitor adherence COVID-19 public health guidelines content analysis policy |
| DOI | 10.2196/24787 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Institute of Allergy and Infectious Diseases (NIAID) ; National Institute on Drug Abuse (NIDA) |
| Funding Organization | National Institute of Allergy and Infectious Diseases (NIAID) ; National Institute on Drug Abuse (NIDA) |
| WOS Research Area | Health Care Sciences & Services ; Medical Informatics |
| WOS Subject | Health Care Sciences & Services ; Medical Informatics |
| WOS ID | WOS:000790206800001 |
| Publisher | JMIR PUBLICATIONS, INC |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/48410 |
| Collection | 复杂系统管理与控制国家重点实验室_互联网大数据与信息安全 |
| Corresponding Author | Young, Sean D. |
| Affiliation | 1.Univ Calif Irvine, Univ Calif Inst Predict Technol, Dept Informat, 6091 Bren Hall, Irvine, CA 92617 USA 2.Univ Calif Irvine, Dept Emergency Med, Irvine, CA USA 3.City Univ Hong Kong, Sch Data Sci, Kowloon, Hong Kong, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 5.Calif Polytech State Univ San Luis Obispo, Dept Informat Syst, San Luis Obispo, CA USA 6.Univ Calif Los Angeles, Dept Biostat, Los Angeles, CA USA |
| Recommended Citation GB/T 7714 | Young, Sean D.,Zhang, Qingpeng,Zeng, Daniel Dajun,et al. Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis[J]. JOURNAL OF MEDICAL INTERNET RESEARCH,2022,24(3):5. |
| APA | Young, Sean D.,Zhang, Qingpeng,Zeng, Daniel Dajun,Zhan, Yongcheng,&Cumberland, William.(2022).Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis.JOURNAL OF MEDICAL INTERNET RESEARCH,24(3),5. |
| MLA | Young, Sean D.,et al."Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis".JOURNAL OF MEDICAL INTERNET RESEARCH 24.3(2022):5. |
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