This thesis addresses the issue of automatically identifying media bias, mostly linguistic bias, in news articles. A varying word choice in any news content may have a major effect on the public and individual perception of societal issues, especially since regular news consumers are mostly unaware of the degree and scope of bias. Detecting and highlighting media bias is generally a challenging task since it is context-dependent, can be expressed in many ways, and its perception even differs based on personal perception and background.