Revealing public attitudes toward mobile cabin hospitals during Covid-19 pandemic: Sentiment and topic analyses using social media data in China

Shenghua Zhou, Hongyu Wang, Dezhi Li*, S. Thomas Ng, Ran Wei, Yongheng Zhao, Yubo Zhou

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

14 Citations (Scopus)

Abstract

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.
Original languageEnglish
Article number105440
JournalSustainable Cities and Society
Volume107
Online published12 Apr 2024
DOIs
Publication statusPublished - 15 Jul 2024

Funding

The authors wish to express sincere gratitude for the financial support from the National Natural Science Foundation of China (No. 72201057) and Collaborative Research Fund from Hong Kong University Grants Committee (No. 8730069). Thank Dr. Prince Antwi-Afari and Dr. Kabir Adamu for their proofreading work. All supplemental materials including collected SMD, shared codes, and developed models are available in the GitHub repository (https://github.com/0AnonymousSite0/Mining-Social-Media-Data-for-Revealing-Public-Attitudes-toward-Mobile-Cabin-Hospitals).

Research Keywords

  • Mobile cabin hospital
  • Public attitude
  • Sentiment
  • Social media
  • Topic

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