DEMON, acronym for Democratic Estimation of the Modular Organization of a Network, is a static community discovery algorithm that falls in the Model-based approach. The novelty of the algorithm is the fact that communities are discovered in a ”democratic” fashion: each node of the network proposes a set of communities based on its local view. Then these local communities are merged together to build the global communities.
The algorithm uses two useful concepts: the Ego Network, the same we presented in section 4, and the Ego Minus Ego. The ego minus ego of a node u can be obtained from its ego network by simply removing node u itself and all its incident edges. The ego minus ego of a user u is therefore the set of its alters with the interactions between them.
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GUIDI, Barbara, MICHIENZI, Andrea and ROSSETTI, Giulio, 2019. Towards the Dynamic Community Discovery in Decentralized Online Social Networks. Journal of Grid Computing. March 2019. Vol. 17, no. 1, p. 23–44. DOI 10.1007/s10723-018-9448-0. [Accessed 21 March 2024].
DEMON (04) stands for Democratic Estimate of the Modular Organization of Network. DEMON is a first local method for finding community in a large scale graph and work on ego network. This algorithm contains mainly two phases. In the First phase, the label propagation algorithm (07) is applied for detecting the local communities on ego-minus-ego networks of the graph. An ego network converts an ego-minus-ego network if ego nodes with their edges are removed from the ego network. Now resultant communities of these ego-minusego networks are mixed to get the global community.
GUPTA, Bipin and SINGH, Ashutosh, [no date]. COMPARATIVE ANALYSIS OF COMMUNITY DETECTION. pdf 