It is widely thought that news organizations exhibit ideological bias, but rigorously quantifying such slant has proven methodologically challenging. Through a combination of machinelearning and crowdsourcing techniques, we investigate the selection and framing of political issues in fifteen major US news outlets. Starting with 803,146 news stories published over twelve months, we first used su...

Researchers are rapidly developing new automated techniques to scale political speech on an ideological dimension. Yet, the task has proven difficult across many settings. Political advertisements, in particular, have eluded such efforts. Candidates air relatively few ads, containing limited policy information, and there is little agreement about how to model political speech in the campaign, m...