报纸
中国
政治学
公共关系
媒体研究
社会学
法学
标识
DOI:10.1080/19331681.2020.1756553
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI