Title: Social Networks through the Prism of Cognition,
Abstract: Human relations are driven by social events - people interact, exchange
information, share knowledge and emotions, or gather news from mass media.
These events leave traces in human memory. The initial strength of a trace
depends on cognitive factors such as emotions or attention span. Each trace
continuously weakens over time unless another related event activity
strengthens it. Here, we introduce a novel Cognition-driven Social Network
(CogSNet) model that accounts for cognitive aspects of social perception and
explicitly represents human memory dynamics. For validation, we apply our model
to NetSense data on social interactions among university students. The results
show that CogSNet significantly improves quality of modeling of human
interactions in social networks.