This paper reports on the linguistic analysis of a tag set of nearly 50,000 tags collected as part of the steve.museum project. The tags describe images of objects in museum collections. We present our results on morphological, part of speech and semantic analysis. We demonstrate that deeper tag processing provides valuable information for organizing and categorizing social tags. This promises to improve access to museum objects by leveraging the characteristics of tags and the relationships between them rather than treating them as individual items. The paper shows the value of using deep computational linguistic techniques in interdisciplinary projects on tagging over images of objects in museums and libraries. We compare our data and analysis to Flickr and other image tagging projects.