Media coverage in times of political crisis: A text mining approach

摘要

At the year end of 2011 Belgium formed a government, after a world record breaking period of 541 days of negotiations. We have gathered and analysed 68,000 related on-line news articles published in 2011 in Flemish newspapers. These articles were analysed by a custom-built expert system. The results of our text mining analyses show interesting differences in media coverage and votes for several political parties and politicians. With opinion mining, we are able to automatically detect the sentiment of each article, thereby allowing to visualise how the tone of reporting evolved throughout the year, on a party, politician and newspaper level. Our suggested framework introduces a generic text mining approach to analyse media coverage on political issues, including a set of methodological guidelines, evaluation metrics, as well as open source opinion mining tools. Since all analyses are based on automated text mining algorithms, an objective overview of the manner of reporting is provided. The analysis shows peaks of positive and negative sentiments during key moments in the negotiation process.