Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Recovering temporally rewiring networks: a model-based approach
Proceedings of the 24th international conference on Machine learning
Unveiling facebook: a measurement study of social network based applications
Proceedings of the 8th ACM SIGCOMM conference on Internet measurement
User interactions in social networks and their implications
Proceedings of the 4th ACM European conference on Computer systems
Beyond friendship graphs: a study of user interactions in Flickr
Proceedings of the 2nd ACM workshop on Online social networks
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
Hot today, gone tomorrow: on the migration of MySpace users
Proceedings of the 2nd ACM workshop on Online social networks
Discrete temporal models of social networks
ICML'06 Proceedings of the 2006 conference on Statistical network analysis
Measurement-calibrated graph models for social network experiments
Proceedings of the 19th international conference on World wide web
Evolution of social-attribute networks: measurements, modeling, and implications using google+
Proceedings of the 2012 ACM conference on Internet measurement conference
Evolution of a location-based online social network: analysis and models
Proceedings of the 2012 ACM conference on Internet measurement conference
Beyond friendship: modeling user activity graphs on social network-based gifting applications
Proceedings of the 2012 ACM conference on Internet measurement conference
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While various models have been proposed for generating social/friendship network graphs, the dynamics of user interactions through online social network (OSN) based applications remain largely unexplored. We previously developed a growth model to capture static weekly snapshots of user activity graphs (UAGs) using data from popular Facebook gifting applications. This paper presents a new continuous graph evolution model aimed to capture microscopic user-level behaviors that govern the growth of the UAG and collectively define the overall graph structure. We demonstrate the utility of our model by applying it to forecast the number of active users over time as the application transitions from initial growth to peak/mature and decline/fatique phase. Using empirical evaluations, we show that our model can accurately reproduce the evolution trend of active user population for gifting applications, or other OSN applications that employ similar growth mechanisms. We also demonstrate that the predictions from our model can guide the generation of synthetic graphs that accurately represent empirical UAG snapshots sampled at different evolution stages.