Characterizing temporally fragmented human activity networks in cyber space using uniform resource locator (URL) data

Abstract

In recent decades, Digital transformation has significantly shifted human activities from physical space to cyber space. When users access the internet, uniform resource locator (URL) data are autogenerated. Using URLs, this study presents a novel framework for exploring cyber space structure from the perspectives of complex networks and activity fragmentation. Web domains within URL data are metaphorically regarded as ‘digital locations,’ and consecutive digital locations form ‘cyber trajectories.’ Human activities that occur at digital locations are semantically labeled and used to generate activity-based motifs. Motifs are defined as frequently occurring processes in cyber trajectories. Based on this, three network types are constructed: Global cyber human activity network, including all trajectories, and space-dependent and motif-dependent cyber human activity networks, focusing on specific regions and motifs. A case study conducted in Jilin, China, using approximately 4.3 gigabytes of URL data, revealed: 1) Cyber human activity patterns exhibit strong regularity and clustering of several types, with metropolitan regions favoring simpler patterns; 2) Cyber human activity networks demonstrate heavy-tailed and hierarchically polycentric structures; 3) The importance of websites in information dissemination increases super linearly along with their increased connectivity. This work deepens our understanding of cyber space functionality, offering insights into cyber information propagation.