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Assessing smoking-related behaviours using massive online search query data

  • Ting Zhou
  • , Long Chen
  • , Zhaoxi Zhang
  • , Zhengying Liu
  • , Ying Long (Corresponding author)

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Online search queries have been used in various behaviour studies. As smoking has become a global health issue, studies that assess smoking-related behaviours using online search queries have faced limitations in data utilization and study design. This study conducts comparative analyses to investigate changes in smoking-related behaviours represented by online search volumes. Baidu search queries from 2013 to 2017 were used to examine the search volume containing four groups of smoking-related search keywords. A validation process was used to validate the proposed method by comparing changes in search queries with the observed tobacco consumption. The results show changes in smoking-related behaviours assessed by online search queries at the city level in China. The validation experiments illustrate the consistency between changes in search volumes and tobacco consumption. Thus, online search queries were verified to be an effective instrument for assessing smoking-related behaviours, and this study sheds light on broader behaviour studies and policy assessments.
Original languageEnglish
Pages (from-to)140-151
JournalTransactions in Urban Data, Science, and Technology
Volume2
Issue number2-3
DOIs
Publication statusPublished - Jun 2023

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