  In this paper, we explore the task of gender classification using limited
network data with an application to Fotolog. We take a heuristic approach to
automating gender inference based on username, followers and network structure.
We test our approach on a subset of 100,000 nodes and analyze our results to
find that there is a lot of value in these limited information and that there
is great promise in further pursuing this approach to classification.
