Recommender systems try to address the "new user problem" by quickly
and painlessly learning user preferences so that users can begin
receiving recommendations as soon as possible. We take an expanded
perspective on the new user experience, seeing it as an opportunity to
elicit valuable contributions to the community and shape subsequent
user behavior. We conducted a field experiment in MovieLens where we
imposed additional work on new users: not only did they have to rate
movies, they also had to enter varying numbers of tags. While requiring
more work led to fewer users completing the entry process, the benefits
were significant: the remaining users produced a large volume of tags
initially, and continued to enter tags at a much higher rate than a
control group. Further, their rating behavior was not depressed. Our
results suggest that careful design of the initial user experience can
lead to significant benefits for an online community.