Intermedia agenda setting is a widely used theory to explain how content transfers between news media. The recent digitalization wave, however, challenges some of its basic presuppositions. We discuss three assumptions that cannot be applied to online and social media unconditionally: one, that media agendas should be measured on an issue level; two, that fixed time lags suffice to understand overlap in media content; and three, that media can be considered homogeneous entities. To address these challenges, we propose a “news story” approach as an alternative way of mapping how news spreads through the media. We compare this with a “traditional” analysis of time-series data. In addition, we differentiate between three groups of actors that use Twitter. For these purposes, we study online and offline media alike, applying both measurement methods to the 2014 Belgium election campaign. Overall, we find that online media outlets strongly affect other media that publish less often. Yet, our news story analysis emphasizes the need to look beyond publication schemes. “Slow” newspapers, for example, often precede other media’s coverage. Underlining the necessity to distinguish between Twitter users, we find that media actors on Twitter have vastly more agenda-setting influence than other actors do.
Intermedia Agenda-Setting Meets R Studio: Computurize Cross-Lagged Correlation Using Rozelle-Campbell Baseline
