Treehugger or petrolhead?: identifying bias by comparing online news articles with political speeches.

The Web is a very democratic medium of communication allowing everyone to express his or her opinion about any type of topic. This multitude of voices makes it more and more important to detect bias and help Internet users understand the background of information sources. Political bias of Web sites, articles, or blog posts is hard to identify straightaway. Manual content analysis conducted by experts is the standard way in political and social science to detect this bias. In this paper we present an automated approach relying on methods from information retrieval and corpus statistics to identify biased vocabulary use. As an example, we analyzed 15 years of parliamentary speeches of the German Bundestag and we investigated whether there is bias towards a political party in major national online newspapers and magazines. The results show that bias exists with respect to vocabulary use and it coincides with human judgement.