Content area
Abstract
Political candidates communicate across a wide number of platforms during their campaigns, including television, Facebook, Twitter, debates, radio, and newspapers. However, these platforms are not the same. Each is made up of a number of different technical features and user affordances. Technical features shape the type of content that can be transmitted through each platform and user affordances describe how platforms are interpreted and used by candidates. The interaction between features and affordances suggests that content ought to vary across platforms, even when the user of those platforms is the same.
I argue in this project that the interaction of features and affordances inclines platforms towards certain ideological audiences and allows for interactions between candidates. I term these the audience and channel of the platform. Audience can range from narrow to broad indicating the degree to which the audience is ideologically homogenous. Channel goes from shared to independent as an indication of how easily candidates can directly interact with their opponents.
I find that broad audience platforms with independent channels are, on average, more negative than narrow audience, shared channel platforms. I also find that policy content is more present in broad audience platforms. Finally, I find that visual communications also exhibit similar patterns. Broad audience and independent channel platforms are markedly more negative and contain more policy language than narrow audience and shared channel platforms. These findings stand up with multiple test of robustness, including different dictionary specifications, word counts, and different elections.
These findings suggest that audiences are being exposed to systematically different content, depending on where they get their information from. This could have meaningful and serious implications for our understanding of political knowledge, polarization, candidate evaluations, and voting. I offer the Platform Audience and Channel Theory as a tool for researchers to study current platforms and a way to understand platforms that have not yet been developed.
