I am using the cluster_infomap algorithm for community detection on a directed graph with 5602 vertices and 42752 links. I have read that this algorithm is not necessarily ideal for a graph of this size, but since our graph is directed, our options are limited.
I ran the algorithm a handful of times, and while I got slightly different results each time, they were results that made sense in the context in our data. Then RStudio crashed, and I lost the communities I’d gotten before. When I ran the algorithm again, all of a sudden the communities were completely different. (We are dealing with musical influence data. Our initial communities very clearly had similarities in the artists that were being clustered into each community, where as I scrolled through the list sorted by community membership, I could tell immediately “okay, this is now a new community”. When I ran it again, that was no longer the case.)
I know that the only way to ensure that we are able to replicate the exact communities each time is to set a specific seed, but I’m really perplexed about how our community structure has changed so drastically. Does anyone have any input, or suggestions about how to get the original community structure back? Thank you!