摘要：En Chile no existe una instancia independiente que publique, constantemente, estudios cuantitativos o cualitativos para comprender el ecosistema de medios tradicionales y sus adaptaciones en la Web Social. Los públicos consumen informaciones ya no sólo en periódicos y noticieros, sino también a partir de redes sociales como su fuente primaria de acceso a la información. Twitter es la red social de noticias por excelencia y los medios hacen esfuerzos por ganar adeptos en ella. En este artículo se propone una metodología basada en minería de datos web. Utilizamos técnicas de rastreo y extracción de flujos de noticias de 37 medios de comunicación chilenos que presentan una vida activa en Twitter y proponemos varios indicadores para compararlos. Analizamos los volúmenes de producción, sus audiencias potenciales y, usando técnicas de procesamiento natural del lenguaje, exploramos el contenido de la producción informativa, sus tendencias editoriales y cobertura geográfica.
其他摘要：In Chile, there is no independent entity that publishes quantitative or qualitative studies that can provide the tools to understand how the traditional media environment has adapted to the social web. Nowadays, Chilean newsreaders are increasingly using social networks as their primary source of information. In this regard, Twitter plays a central role as it is considered, among the users, as the most influential news source on social networks; consequently, mainstream media are making efforts to develop different strategies to increase their audience and influence on this platform. Nevertheless, it is possible to affirm that there is a lack of tools that can serve to analyze these strategies. The following article intends to propose a methodology based on data mining techniques to provide the tools to carry out the analysis of the new Chilean media environment. Crawling techniques were used to mine news feeds from 37 different Chilean media that are currently active on Twitter; moreover, to provide several indicators to compare them. Thus, the volumes of production were analyzed in terms of their potential audience and NLP techniques were used to explore the contents of production, their publishing standards, and their geographical coverage.
