  Modularity clustering is an essential tool to understand complicated graphs.
However, existing methods are not applicable to massive graphs due to two
serious weaknesses. (1) It is difficult to fully reproduce ground-truth
clusters due to the resolution limit problem. (2) They are computationally
expensive because all nodes and edges must be computed iteratively. This paper
proposes gScarf, which outputs fine-grained clusters within a short running
time. To overcome the aforementioned weaknesses, gScarf dynamically prunes
unnecessary nodes and edges, ensuring that it captures fine-grained clusters.
Experiments show that gScarf outperforms existing methods in terms of running
time while finding clusters with high accuracy.
