Fast Counting of Triangles in Large Real Networks without Counting: Algorithms and Laws

How can we quickly find the number of triangles in a large graph, without actually counting them? Triangles are important for real world social networks, lying at the heart of the clustering coefficient and of the transitivity ratio. However, straight-forward and even approximate counting algorithms can be slow, trying to execute or approximate the equivalent of a 3-way database join. In this paper, we provide two algorithms, the eigentriangle for counting the total number of triangles in a graph, and the eigentrianglelocal algorithm that gives the count of triangles that contain a desired node. Additional contributions include the following: (a) We show that both algorithms achieve excellent accuracy, with up to sime 1000x faster execution time, on several, real graphs and (b) we discover two new power laws (degree-triangle and triangleparticipation laws) with surprising properties.