Anchored by the network agenda setting (NAS) model, this study uses a supervised machine-learning approach to analyze the agendas of major newspapers in China, Japan, and the United States, and discussions in Twittersphere, on the Diaoyu/Senkaku Islands dispute, as well as their intermedia effects. Network analyses suggested that Chinese media portrayed the dispute in a more biased way, whereas Twitter’s discussions were overwhelmingly negative. Time-series analyses revealed reciprocities between newspapers and Twitter, while the relationship was asymmetrical where Twitter exerted a stronger bottom-up impact. Moreover, most reciprocities emerged between the U.S. and Chinese media, and Twitter.
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Su et al. (2020) studied this question.
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