TY - JOUR
T1 - Revealing public attitudes toward mobile cabin hospitals during Covid-19 pandemic
T2 - Sentiment and topic analyses using social media data in China
AU - Zhou, Shenghua
AU - Wang, Hongyu
AU - Li, Dezhi
AU - Ng, S. Thomas
AU - Wei, Ran
AU - Zhao, Yongheng
AU - Zhou, Yubo
PY - 2024/7/15
Y1 - 2024/7/15
N2 - The diverse and ambivalent public attitudes toward Mobile Cabin Hospitals (MCHs) markedly influence MCHs’ social sustainability. Conventional studies regarding MCHs’ public attitudes rely heavily on survey-based approaches (e.g., questionnaires) that suffer from limited respondents, short durations, and narrow geographical coverages, overlooking tempo-spatial variations of MCHs’ public attitudes. Hence, this study proposes a social media data (SMD)-based approach to reveal public attitudes toward MCHs. It consists of MCH-related SMD collection, SMD preprocessing and annotation, sentiment and topic analysis model development, model performance verification, and statistical analyses of public sentiments and topics. This newly devised approach has been demonstrated for mining 413,572 pieces of MCH-related SMD covering MCH policy lifecycle in China. The findings reveal that (i) positive sentiment can surpass or fall below negative sentiments toward MCHs, which is correlated with the number of Covid-19 cases (NoCC), and (ii) the rankings of public concerns on 8 positive topics shift between two patterns temporally and spatially with NoCC, while the rankings among 6 negative topics remain stable for China's MCHs. This study not only offers an SMD-based supplementary approach for exploring public attitudes toward MCHs but also updates current understandings to enhance their social sustainability. © 2024 Elsevier Ltd.
AB - The diverse and ambivalent public attitudes toward Mobile Cabin Hospitals (MCHs) markedly influence MCHs’ social sustainability. Conventional studies regarding MCHs’ public attitudes rely heavily on survey-based approaches (e.g., questionnaires) that suffer from limited respondents, short durations, and narrow geographical coverages, overlooking tempo-spatial variations of MCHs’ public attitudes. Hence, this study proposes a social media data (SMD)-based approach to reveal public attitudes toward MCHs. It consists of MCH-related SMD collection, SMD preprocessing and annotation, sentiment and topic analysis model development, model performance verification, and statistical analyses of public sentiments and topics. This newly devised approach has been demonstrated for mining 413,572 pieces of MCH-related SMD covering MCH policy lifecycle in China. The findings reveal that (i) positive sentiment can surpass or fall below negative sentiments toward MCHs, which is correlated with the number of Covid-19 cases (NoCC), and (ii) the rankings of public concerns on 8 positive topics shift between two patterns temporally and spatially with NoCC, while the rankings among 6 negative topics remain stable for China's MCHs. This study not only offers an SMD-based supplementary approach for exploring public attitudes toward MCHs but also updates current understandings to enhance their social sustainability. © 2024 Elsevier Ltd.
KW - Mobile cabin hospital
KW - Public attitude
KW - Sentiment
KW - Social media
KW - Topic
UR - http://www.scopus.com/inward/record.url?scp=85190319117&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85190319117&origin=recordpage
U2 - 10.1016/j.scs.2024.105440
DO - 10.1016/j.scs.2024.105440
M3 - RGC 21 - Publication in refereed journal
SN - 2210-6707
VL - 107
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 105440
ER -