In this paper, we provide a detailed analysis of PageRank to determine the relevance of arguments along with content- and knowledge-based methods from the field of natural language processing. We do not only show how the cross-linking of arguments is only slightly involved in the recognition of relevance, we rather show how basic common knowledge and reader-involving methods outperform the purely structure-related PageRank. The methods we propose are based on the latest research and correlate strongly with human awareness regarding the relevance of arguments. Altogether, we show that PageRank does not fully capture the relevance of arguments and must be extended by a contextual level in order to take concepts of natural language into account at the web level, as they are unavoidably involved in argumentation.