  Recent research has shown the usefulness of social tags as a data source to
feed resource classification. Little is known about the effect of settings on
folksonomies created on social tagging systems. In this work, we consider the
settings of social tagging systems to further understand tag distributions in
folksonomies. We analyze in depth the tag distributions on three large-scale
social tagging datasets, and analyze the effect on a resource classification
task. To this end, we study the appropriateness of applying weighting schemes
based on the well-known TF-IDF for resource classification. We show the great
importance of settings as to altering tag distributions. Among those settings,
tag suggestions produce very different folksonomies, which condition the
success of the employed weighting schemes. Our findings and analyses are
relevant for researchers studying tag-based resource classification, user
behavior in social networks, the structure of folksonomies and tag
distributions, as well as for developers of social tagging systems in search of
an appropriate setting.
