Anita captured succinctly the area of social network data, how graph data is complex and what goes into analyzing sharing and why do we even care about sharing trends.
Some quick points from her presentation
Susceptible infected recovery model is used to figure out how the sharing of black and blue dress blew out worldwide.
They have big graphs and they use recursive algorithms and parallel processing to compute.
By doing this analysis they are able to go towards understanding user behavior. For example sharing behavior of women and men.
The articles get shared because it resonates on a deep human level and that’s fascinating.
Graph algorithms to understand causes of virality of different assets, and measure sharing across different data sources.