
Scholars have long questioned whether the traditional media effects approach can still be applied in the current digital media era, especially in the non-Western, state-regulated Chinese media environment. This study examines the intermedia agenda setting of traditional media sources and we-media sources in the WeChat Official Accounts through a computational look at the Changsheng Bio-technology vaccine (CBV) crisis. Utilizing LDA topic modeling and Granger causality analysis, results show that both traditional media and we-media (i.e., online news sources operated by individuals or collectives) focus more consistently on two frames, the news facts and the countermeasure and suggestion frames. Interestingly, the traditional media agenda impacts the we-media agenda under the news fact and the countermeasure and suggestion frames, while the we-media agenda influences the traditional media agenda under the moral judgment and causality background frames. Overall, our study demonstrates the mutual effects between the traditional media agenda and the we-media agenda. This study sheds light on the theoretical meaning of network agenda setting and extends its application to social media platforms in Eastern countries and health-related fields.
network agenda setting, Internet, Vaccines, LDA modeling, Vaccination, Article, Asian People, vaccine, Humans, intermedia agenda setting, Mass Media, Social Media
network agenda setting, Internet, Vaccines, LDA modeling, Vaccination, Article, Asian People, vaccine, Humans, intermedia agenda setting, Mass Media, Social Media
| 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). | 5 | |
| 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. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
