Discovering Communities in Social Networks Using Topology and Attributes

Rumour prevention in social networks with layer 2 blockchains

“…In Comito et al (2019) an algorithm to identify social neighbourhood using word embedding is proposed. Salem et al (2011) proposed a community discovery algorithm using network topology. Schreckenberger et al (2018) presents a survey on predicting the next location of users in location-based social networks.…”

An IAC Approach for Detecting Profile Cloning in Online Social Networks

“…It is obvious that network topological structure and attribute information can be used to identify some hidden patterns in communities. In this study, IAC clustering algorithm [11] is applied to detect communities in social network graphs. Figure 2 shows a pseudo code of the algorithm where it accepts an attribute augmented graph and return a clustered graph as output.…”

“…Figure 2. IAC Clustering Algorithm [11] An augmented graph is a graph G = (V, E, ߯), where V = {v 1 , v 2 , v 3 , …,v n } is the set of nodes and n = |V| denotes the number of nodes in the graph, E ⊂ V× V is the set of edges,E = {(v i , v j ): v i , v j ∈V}, and ߯∈ R |v| × d is the nodes attribute matrix. First of all, the algorithm creates the similarity matrix C, then according to K (K = ߙ× E) it adds the set of edges to the graph and the elements which belong to these edges are set to 1 in matrix S. As well as matrix W is made by summation of S and A.…”

Trust levels in social networks

“…One may refer to Refs. [ [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] ] for recent research on topological aspects of social networks. Also [ 14 , 15 ], can be considered to find connections between social networks and computer science.…”