Graph Neural Network for Crawling Target Nodes in Social Networks.
Kirill LukyanovMikhail DrobyshevskiyDanil ShaikhelislamovDenis TurdakovPublished in: CoRR (2024)
Keyphrases
- social networks
- neural network
- web graph
- directed graph
- betweenness centrality
- massive graphs
- graph structure
- heterogeneous social networks
- social graphs
- real world social networks
- small world
- overlapping communities
- adjacency matrix
- social network analysis
- undirected graph
- weighted graph
- shortest path
- network structure
- complex networks
- online social networks
- graph mining algorithms
- real world networks
- nodes of a graph
- connected graphs
- evolving graphs
- strongly connected
- ranking algorithm
- graph mining
- back propagation
- link prediction
- graph partitioning
- link analysis
- community detection
- random walk
- graph theory
- neural network model
- network properties
- artificial neural networks
- web pages
- root node
- social relationships
- graph structures
- random graphs
- information propagation
- centrality measures
- search engine
- path length
- information diffusion
- community structure
- edge weights
- bipartite graph
- fully connected
- social media
- communities in social networks
- finding the shortest path
- social networking
- graph matching
- reachability queries
- network model
- directed acyclic graph
- planar graphs
- clustering coefficient
- graph clustering
- social groups
- graph databases
- spanning tree
- diffusion process
- attributed graphs
- maximum flow
- social graph
- connected components
- web mining
- structured data
- community discovery