An Ontology-Based Computational Framework for Analyzing Public Opinion Framing in News Media

The aim of this study is to develop a computational framework for analyzing the framing of news coverage for controversial public issues by comparing the coverage from ideologically distant news media sources. Because news media sources play a key role in the formation of public opinion, their coverage also plays a major role in the dynamics of the public debates. It can be hypothesized that the public interactions of political players may be treated differently in the media based on the editorial perspective of the media sources in question and the positions that the political players occupy in the political arena. However, the question arises, how can these differences be measured? Using corpus extraction techniques, SPARQL queries, and ontology engineering, this study compares the positions that key political players occupy in discourse spaces that are modeled by two ideologically distant news media sources based on the same controversial public issue.