1. Community detection algorithms are used to identify natural groupings or communities within graph data based on connections between nodes. These algorithms decide which nodes are part of the same community.
2. There are different approaches to defining communities, ranging from strict rules like nodes being directly connected to all other community members, to more lenient rules like relative density measured by modularity.
3. Community detection identifies clusters rather than strict partitions, so some nodes may belong to multiple communities or no community. The algorithms help uncover the natural boundaries between communities in the graph.