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

TitleSocial Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis
Authors
Keywordsadherence
content analysis
COVID-19
guidelines
health informatics
internet
monitor
policy
public health
social media
tool
Issue Date2022
Citation
Journal of Medical Internet Research, 2022, v. 24, n. 3, article no. e24787 How to Cite?
AbstractBackground: 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.
Persistent Identifierhttp://hdl.handle.net/10722/330773
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYoung, Sean D.-
dc.contributor.authorZhang, Qingpeng-
dc.contributor.authorZeng, Daniel Dajun-
dc.contributor.authorZhan, Yongcheng-
dc.contributor.authorCumberland, William-
dc.date.accessioned2023-09-05T12:14:07Z-
dc.date.available2023-09-05T12:14:07Z-
dc.date.issued2022-
dc.identifier.citationJournal of Medical Internet Research, 2022, v. 24, n. 3, article no. e24787-
dc.identifier.urihttp://hdl.handle.net/10722/330773-
dc.description.abstractBackground: 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.-
dc.languageeng-
dc.relation.ispartofJournal of Medical Internet Research-
dc.subjectadherence-
dc.subjectcontent analysis-
dc.subjectCOVID-19-
dc.subjectguidelines-
dc.subjecthealth informatics-
dc.subjectinternet-
dc.subjectmonitor-
dc.subjectpolicy-
dc.subjectpublic health-
dc.subjectsocial media-
dc.subjecttool-
dc.titleSocial Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: Content Analysis-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.2196/24787-
dc.identifier.pmid34995205-
dc.identifier.scopuseid_2-s2.0-85125682887-
dc.identifier.volume24-
dc.identifier.issue3-
dc.identifier.spagearticle no. e24787-
dc.identifier.epagearticle no. e24787-
dc.identifier.eissn1438-8871-
dc.identifier.isiWOS:000790206800001-

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