Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review

Social network analysis (SNA), or the application of network analysis techniques to social media data, is an increasingly prominent approach used in computational public health research. We conducted a systematic review to investigate trends around SNA applied to social media data for public health...

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Main Authors: Stanislava Gardasevic, Aditi Jaiswal, Manika Lamba, Jena Funakoshi, Kar-Hai Chu, Aekta Shah, Yinan Sun, Pallav Pokhrel, Peter Washington
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Information
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Online Access:https://www.mdpi.com/2078-2489/15/11/690
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author Stanislava Gardasevic
Aditi Jaiswal
Manika Lamba
Jena Funakoshi
Kar-Hai Chu
Aekta Shah
Yinan Sun
Pallav Pokhrel
Peter Washington
author_facet Stanislava Gardasevic
Aditi Jaiswal
Manika Lamba
Jena Funakoshi
Kar-Hai Chu
Aekta Shah
Yinan Sun
Pallav Pokhrel
Peter Washington
author_sort Stanislava Gardasevic
collection DOAJ
description Social network analysis (SNA), or the application of network analysis techniques to social media data, is an increasingly prominent approach used in computational public health research. We conducted a systematic review to investigate trends around SNA applied to social media data for public health and epidemiology while outlining existing ethical practices. Following PRISMA guidelines, we reviewed articles from Web of Science and PubMed published between January 2019 and February 2024, leading to a total of 51 papers surveyed. The majority of analyzed research (69%) involved studying Twitter/X, followed by Sina Weibo (16%). The most prominent topics in this timeframe were related to COVID-19, while other papers explored public health topics such as citizen science, public emergencies, behavior change, and various medical conditions. We surveyed the methodological approaches and network characteristics commonly employed in public health SNA studies, finding that most studies applied only basic network metrics and algorithms such as layout, community detection, and standard centrality measures. We highlight the ethical concerns related to the use of social media data, such as privacy and consent, underscoring the potential of integrating ethical SNA with more inclusive, human-centered practices to enhance the effectiveness and community buy-in of emerging computational public health efforts.
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spelling doaj-art-5c26dfc22e5d4cda9aad9c339fa6f5f72024-11-26T18:06:35ZengMDPI AGInformation2078-24892024-11-01151169010.3390/info15110690Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic ReviewStanislava Gardasevic0Aditi Jaiswal1Manika Lamba2Jena Funakoshi3Kar-Hai Chu4Aekta Shah5Yinan Sun6Pallav Pokhrel7Peter Washington8Communication and Information Sciences, University of Hawai’i at Mānoa, Honolulu, HI 96822, USAInformation and Computer Sciences, University of Hawai’i at Mānoa, Honolulu, HI 96822, USASchool of Library & Information Studies, University of Oklahoma, Norman, OK 73019, USAOffice of Public Health Studies, University of Hawai’i at Mānoa, Honolulu, HI 96822, USABehavioral and Community Health Sciences, Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA 15260, USAUnaffiliated Researcher, Oakland, CA 94612, USACommunication and Information Sciences, University of Hawai’i at Mānoa, Honolulu, HI 96822, USAUniversity of Hawai’i Cancer Center, University of Hawai’i at Mānoa, Honolulu, HI 96822, USAInformation and Computer Sciences, University of Hawai’i at Mānoa, Honolulu, HI 96822, USASocial network analysis (SNA), or the application of network analysis techniques to social media data, is an increasingly prominent approach used in computational public health research. We conducted a systematic review to investigate trends around SNA applied to social media data for public health and epidemiology while outlining existing ethical practices. Following PRISMA guidelines, we reviewed articles from Web of Science and PubMed published between January 2019 and February 2024, leading to a total of 51 papers surveyed. The majority of analyzed research (69%) involved studying Twitter/X, followed by Sina Weibo (16%). The most prominent topics in this timeframe were related to COVID-19, while other papers explored public health topics such as citizen science, public emergencies, behavior change, and various medical conditions. We surveyed the methodological approaches and network characteristics commonly employed in public health SNA studies, finding that most studies applied only basic network metrics and algorithms such as layout, community detection, and standard centrality measures. We highlight the ethical concerns related to the use of social media data, such as privacy and consent, underscoring the potential of integrating ethical SNA with more inclusive, human-centered practices to enhance the effectiveness and community buy-in of emerging computational public health efforts.https://www.mdpi.com/2078-2489/15/11/690public healthepidemiologyCOVID-19social network analysissocial media
spellingShingle Stanislava Gardasevic
Aditi Jaiswal
Manika Lamba
Jena Funakoshi
Kar-Hai Chu
Aekta Shah
Yinan Sun
Pallav Pokhrel
Peter Washington
Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review
Information
public health
epidemiology
COVID-19
social network analysis
social media
title Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review
title_full Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review
title_fullStr Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review
title_full_unstemmed Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review
title_short Public Health Using Social Network Analysis During the COVID-19 Era: A Systematic Review
title_sort public health using social network analysis during the covid 19 era a systematic review
topic public health
epidemiology
COVID-19
social network analysis
social media
url https://www.mdpi.com/2078-2489/15/11/690
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