Evolutionary dynamics on sequential temporal networks
Fig 5
Evolution of cooperation in four empirical datasets.
We analyze four empirical datasets from different social contexts: a scientific conference in Nice, France [45], the Science Gallery in Dublin, Ireland [46], a workplace in two different years in France [47]. a, the sequential temporal networks promote the evolution of cooperation for any number of rounds g in these datasets. The corresponding fixation probabilities are monotonically increasing with respect to the parameter g. Parameter values are δ = 0.025 for the first dataset, δ = 0.01 for the remaining datasets, and c = 1 for all datasets. b-c, We present the structure of the sequential temporal networks for the first (b) and third datasets (c). The number of nodes and the average degree at time t are denoted as N(t) and k(t), respectively.