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. 2022 Mar 3;24(3):e24787.
doi: 10.2196/24787.

Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis

Sean D Young  1   2 , Qingpeng Zhang  3 , Daniel Dajun Zeng  4 , Yongcheng Zhan  5 , William Cumberland  6
Affiliations

Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis

Sean D Young et al. J Med Internet Res. .

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.

Keywords: COVID-19; adherence; content analysis; guidelines; health informatics; internet; monitor; policy; public health; social media; tool.

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Conflict of interest statement

Conflicts of Interest: SDY has received equity in MotiSpark, a company that uses images/videos for health behavior change. SDY has been a previous recipient of gift funding from Facebook (funding was made to the University of California with SDY as PI).

Figures

Figure 1
Figure 1
Number of images posted to the location hashtags over time, New York, 2020. Trendlines are estimated by a third-order polynomial function.
See this image and copyright information in PMC

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