Diagnosing editorial strategies of Chilean media on Twitter using an
  automatic news classifier
  In Chile, does not exist an independent entity that publishes quantitative or
qualitative surveys to understand the traditional media environment and its
adaptation on the Social Web. Nowadays, Chilean newsreaders are increasingly
using social web platforms as their primary source of information, among which
Twitter plays a central role. Historical media and pure players are developing
different strategies to increase their audience and influence on this platform.
In this article, we propose a methodology based on data mining techniques to
provide a first level of analysis of the new Chilean media environment. We use
a crawling technique to mine news streams of 37 different Chilean media
actively presents on Twitter and propose several indicators to compare them. We
analyze their volumes of production, their potential audience, and using NLP
techniques, we explore the content of their production: their editorial line
and their geographic coverage.
