TY - JOUR
T1 - Social media mining under the COVID-19 context
T2 - Progress, challenges, and opportunities
AU - Huang, Xiao
AU - Wang, Siqin
AU - Zhang, Mengxi
AU - Hu, Tao
AU - Hohl, Alexander
AU - She, Bing
AU - Gong, Xi
AU - Li, Jianxin
AU - Liu, Xiao
AU - Gruebner, Oliver
AU - Liu, Regina
AU - Li, Xiao
AU - Liu, Zhewei
AU - Ye, Xinyue
AU - Li, Zhenlong
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2022/9
Y1 - 2022/9
N2 - Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and reproducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies.
AB - Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and reproducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies.
KW - Big data
KW - COVID-19
KW - Data mining
KW - Pandemic
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=85136642637&partnerID=8YFLogxK
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U2 - 10.1016/j.jag.2022.102967
DO - 10.1016/j.jag.2022.102967
M3 - Article
AN - SCOPUS:85136642637
SN - 1569-8432
VL - 113
JO - International Journal of Applied Earth Observation and Geoinformation
JF - International Journal of Applied Earth Observation and Geoinformation
M1 - 102967
ER -