Effect·Mechanism·Path:A Study on the Dissemination of Data Journalism on Social Platforms
Taking 32 typical cases of data journalism on social platforms as research objects,we use qualitative comparative analysis(QCA)to explore the causative factors and generative processes of data news dissemination in specific platform contexts.Previous studies have focused on the content of data news,and the precontact stage has been neglected and obscured.By focusing on the chronological path of the platform audience's information contact,the main analysis frameworks of"issue reach"and"content perception"are constructed to analyse the causative factors and combination paths of data news dissemination on social platforms from the issue and content levels.The study finds that information dissemination on social platforms has an obvious two-tier introduction pattern,in which the title is the key factor that triggers the influx of user traffic and drives the data news content to achieve a high degree of dissemination,and the two data combination configurations of"composite"and"mining"are more potential for the dissemination.The static infographics are more suitable for the platform context and user preferences.At the same time,the specific and stable paths for data news to achieve high dissemination are sorted out at the micro level,which is of practical significance for breaking the current dilemma of the lack of dissemination of data news on social platforms and improving the overall content dissemination.
data journalismsocial platformqualitative comparative analysis(QCA)dissemination
万方数据
维普
