LDPCD: A Novel Method for Locally Differentially Private Community Detection

Table 1

The description of the main notations used in this article.

Symbols	Descriptions
	The set of all users
	A user subset of
	A bipartition of
	The true/noisy fitness of user i in terms of
	i’s true/noisy degree in
	i’s true/noisy degree vector in
	The estimated modularity of a community division of all users
	The estimated bipartition modularity of
	The final bipartite grouping of with converged
	The community division result of all users of the th round bipartition
	A certain user subset (community) of
	The gain of caused by the substitution of for in user community division
	The privacy budget used for each query on user’s degree vector based on
	The privacy budget used for the query on user’s degree vector based on to estimate