Research methods in the age of digital journalism

News content analysis is usually preceded by a labour-intensive coding phase, where experts extract key information from news items. The cost of this phase imposes limitations on the sample sizes that can be processed, and therefore to the kind of questions that can be addressed. In this paper we describe an approach that incorporates text-analysis technologies for the automation of some of these tasks, enabling us to analyse data sets that are many orders of magnitude larger than those normally used. The patterns detected by our method include: (1) similarities in writing style among several outlets, which reflect reader demographics; (2) gender imbalance in media content and its relation with topic; (3) the relationship between topic and popularity of articles