In this work we study the task of term extraction for word cloud generation. We present a folksonomy-based term extraction method, called tag-boost, which boosts terms that are frequently used by the public to tag content. Our experiments with tag-boost-based term extraction over different domains demonstrate tremendous improvement in word cloud quality, as reflected by the agreement between extracted terms and manually assigned tags of the testing items. Additionally, we show that tag-boost can be effectively applied even in non-tagged domains, by using an external rich folksonomy borrowed from a well-tagged domain. © 2011 ACM.