Big Data & Society (Sep 2024)

Joint-sensemaking, innovation, and communication management during crisis: Evidence from the DCT applications in China

  • Jingjing Qu,
  • Liwei Chen,
  • Hui Zou,
  • Hui Hui,
  • Wen Zheng,
  • Jar-Der Luo,
  • Qingyuan Gong,
  • Yuwei Zhang,
  • Tianyu Wen,
  • Yang Chen

DOI
https://doi.org/10.1177/20539517241270714
Journal volume & issue
Vol. 11

Abstract

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As exemplified by the COVID-19 pandemic, the design and implementation of data-driven health surveillance, like digital contact tracing (DCT) apps, carry significant implications for society. However, its rushed development calls for careful consideration from all involved stakeholders to achieve a shared understanding and engage in joint-sensemaking in order to implement DCT collaboratively and effectively utilize it in the fight against the pandemic. Yet, the empirical ground truth and theoretical mechanism of joint-sensemaking are both unclear. Drawing on this gap, this article applies a multistep approach, including sentiment analysis, topic analysis coupled with regression and unique network analysis, to thoroughly explore, examine, and explain the dynamic process of joint-sensemaking in the context of a public crisis. Based on evidence from 113,264 Weibo posts, we illustrate two joint-sensemaking pathways and three key interventions using the case of China's Health Code in the context of the DCT. We reveal that the effectiveness of different interventions and contributions made by stakeholders vary significantly between different joint-sensemaking pathways. Specifically, we find that official media and opinion leaders act as crucial mediators in bridging intervention conductors and the public. However, their influence presents heterogeneity toward different network modularity, thus leading to distinct patterns. Additionally, inconsistent with previous literature, we find that within the context of the China Health Code, official media has a greater impact on opinion leaders in engaging the public.