A Hybrid Adjacency and Time-Based Data Structure for Analysis of Temporal Networks

Abstract

AbstractDynamic or temporal networks enable representation of time-varying edges between nodes. Conventional adjacency-based data structures used for storing networks such as adjacency lists were designed without incorporating time. When used to store temporal networks, such structures can be used to quickly retrieve all edges between two sets of nodes, which we call a node-based slice, but cannot quickly retrieve all edges that occur within a given time interval, which we call a time-based slice. We propose a hybrid data structure for storing temporal networks with timestamped edges, including instantaneous edges such as messages on social media and edges with duration such as phone calls. Our hybrid structure stores edges in both an adjacency dictionary, enabling rapid node-based slices, and an interval tree, enabling rapid time-based slices. We evaluate our hybrid data structure on many real temporal network data sets and find that they achieve much faster slice times than adjacency-based baseline structures with only a modest increase in creation time and memory usage.KeywordsDynamic graph structureDynamic networkInterval treeAdjacency dictionaryTimestamped networkRelational events