The present study tests the agendamelding theory, which posits that public agenda is the result of a process whereby audiences “meld” agendas from various media along with their personal agenda to form a coherent picture of society. To that end, the contributions of the traditional media agenda, the social media agenda, and the personal agenda of Iranian audiences to their public agenda are independently measured and compared against values predicted by theory. The findings indicate a strong social media agenda-setting effect in Iran ( ρ = .83, p < .05) and a weak, non-significant traditional media agenda-setting effect ( ρ = .28, p = .48). On average, actual contributions closely mirror values predicted by theory, suggesting that agendamelding is a viable theory for studying the audience-media relationship.
This article studies the efficiency of different samples for content analysis of news in media effects studies by comparing the agenda-setting effect of a classic sample with the effect of a sample drawn based on audiences’ self-reported media habits. Contrary to the belief that exposure to sampled media content is necessary for observation of media effects, samples drawn based on overall readership/viewership of the media are more efficient than samples based on audiences’ actual consumption habits. A traditional media sample yields a stronger agenda-setting effect compared to a sample drawn based on self-reported media habits. But correlations between the two media samples are also strong. The findings suggest that a broad intermedia agenda-setting process makes it possible for researchers to draw a traditional sample that is representative of the issues salient to audiences regardless of their level of exposure to the sampled media. In other words, even in a demassified media environment, traditional samples are still the best option for media effects researchers.
Abstract In an effort to understand the legislative agenda setting impacts of social media content, the present study analyzes political discourse on Twitter regarding the George Floyd Justice in Policing Act. Using a Latent Dirichlet Allocation (LDA) topic model to dissect the Twitter conversation aimed at Representative Karen Bass, the sponsor of the H.R.7120, in the weeks leading up to the bill’s filing, our analysis of nearly 68,000 tweets posted in the days before the bill’s filing reveals that constituents strongly urged the Representative to work on legislation targeted on police reform – offering evidence of how constituents demanded, and drove, legislative action. Considering our findings, we argue that there is considerable potential for social media to serve as an amplifier of social issues and concerns among constituents. Through this process, we posit that social media can prove to be a vital catalyst in social justice reform.
