Newspapers create publicity, draw attention to topics, and try to gain thematic acceptance from the reader. To achieve this, they use linguistic strategies and select culturally and historically evolved encyclopedic knowledge sources. In our pilot study we explore the presentation of the events in the Middle East–North African region between December 2010 and November 2011 that were soon metaphorically framed as the Arab Spring. To this end, we use a text corpus consisting of 300 opinion pieces from five national German newspapers. To get access to the conceptual knowledge structure and the linguistic strategies, we combine text mining methods and cognitive linguistics. We focus on conceptual metaphors (Lakoff and Johnson, 1980) and their binary source–target structure, where the source domain reveals the underlying conceptual knowledge structures of the speaker. This research focus is justified by the omnipresence of political abstract nouns and by the consistency of metaphors—in particular, genitive metaphor constructions—within the corpus. We first annotate parts of our corpus for such metaphors. Then, additional genitive metaphors are automatically extracted using an adapted metaphor detection system. Finally, we use a clustering algorithm to group the metaphors by source domain. In the following manual cluster analysis, we show that conceptual metaphors are being used throughout the corpus in a systematic way to implicitly categorize and assess the Arab Spring.