  Large, dense, small-world networks often emerge from social phenomena,
including financial networks, social media, or epidemiology. As networks grow
in importance, it is often necessary to partition them into meaningful units of
analysis. In this work, we propose GUDIE, a message-passing algorithm that
extracts relevant context around seed nodes based on user-defined criteria. We
design GUDIE for rich, labeled graphs, and expansions consider node and edge
attributes. Preliminary results indicate that GUDIE expands to insightful areas
while avoiding unimportant connections. The resulting subgraphs contain the
relevant context for a seed node and can accelerate and extend analysis
capabilities in finance and other critical networks.
