Teaching machines to understand human communication is one of the central goals of artificial intelligence. Psychological research indicates that human associations are an essential requirement to understand human communication. In this paper the hypothesis is presented, that simulating human associations with the help of Linked Data could greatly improve text understanding capabilities of machines. To more thoroughly investigate whether human associations can be simulated with Linked Data, two preliminary problems are identified: (i) There does not seem to be a reasonable ground truth for human associations and (ii) while human associations have different strengths, Linked Data treats all triples equally and does not provide edge weights. Two ideas for games in accordance with Luis von Ahn's Games with a Purpose are proposed, turning the tedious process of entering associations or ratings into fun games.