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Communicating climate change to young adults in China: examining predictors of user engagement on Chinese social media

Authors: ShaoPeng Che; Kai Kuang; Liming Liu; Shujun Liu;

Communicating climate change to young adults in China: examining predictors of user engagement on Chinese social media

Abstract

Purpose This study aims to examine how the Chinese climate nongovernmental organization “Chinese Weather Enthusiasts” engaged youth through video strategies. Design/methodology/approach The research proposed a framework grounded in the 5W model and message sensation value (MSV) to analyze the relationship between video content and user interaction. It categorized Bilibili videos into outer and inner features and introduced rhetorical strategies as content elements. A hybrid video coding framework was used, combining machine learning and deep learning (computer vision) for analyzing formal features, while manual coding was used for content features. Findings The results revealed that video length, long shots and the number of scenes positively influenced coins and favorites, whereas personification had a negative impact. In addition, tone and language intensity were positively correlated with user engagement. Originality/value This study offers insights regarding video production for climate communication, broadening the focus from text and images to video content and providing evidence-based guidance for practitioners.

Related Organizations
Keywords

User engagement, Nongovernmental organization, Environmental sciences, Video production, Meteorology. Climatology, Climate change, Communication strategy, GE1-350, QC851-999, Bilibili

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold