Tag clouds are becoming increasingly popular with websites that utilize social tagging to categorize ever expanding collections of digital information. Tagging has been found to be more adaptable than traditional classification, as well as more prone to serendipitous information discovery. The flexibility of tagging systems allows users to rapidly adopt new terms and engage in extremely dynamic tagging practices, yet tag clouds are not able to represent agile shifts in tagging patterns. Over time, semantic and linguistic changes can modify the meaning and form of tags, and changes in tagging behavior can create disconnects between related tags. By conceiving tagging as a triad: object, user, tag, we completely miss the critical notion of time. Time leads to changes in semantics, vocabulary, behavior, and syntax. In order to address the problem of aging tags and aging folksonomies, we really need to include time as a critical facet of tagging: object, user, tag, time. The adaptive behavior of tags requires that there is a constant influx of new descriptive data about an object, but time-related changes have to overcome the weight of the pre-existing tags. In this poster we propose a new tag-cloud visualization technique that attempts to address these issues by including a dynamic factor: the changing weight of tags over time.