The Impact of Climate Change on Media Coverage of Sponge City Programs: A Text Mining and Machine Learning Analysis

Abstract

Sponge city programs (SCPs) are essential for improving urban resilience and sustainability, while media framing can imperceptibly influence public attitudes and thereby influence the smooth implementation of SCPs. Due to socio-political landscapes, media discourse on official and non-official media is different, changing and evolving as emergency events occur. However, few studies have focused on media disclosure differences or investigated the transformation of SCP-related media discourse before and after emergencies. Therefore, based on text mining methods, this study conducts a longitudinal big-data discourse analysis to compare framing differences in state-oriented newspapers and market-oriented web news. A total of 6,413 news articles from July 17th, 2020 to April 17th, 2022 are crawled. The results demonstrate that SCP publicity involves different narratives covering macro-level and micro-level content. After the disaster, attitudes of web news towards SCP are less supportive than those of state-oriented newspapers. Meanwhile, the most salient differences in SCP benefit coverage are social and economic benefits, and the most salient difference in SCP risk coverage is economic risks. Findings provide a retrospective assessment and present valuable practical implications for evidence-based SCP advocacy.

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