Google Research Award
Event Network Models of Social Interaction
Tool-supported social interaction generates massive streams of relational event data. As proxies of user activity such data are assumed to be helpful in understanding and predicting, for instance, the popularity of artifacts (videos, documents, messages, etc.) and the behavior of individuals (activity bursts, churn, inﬂuence, etc.). We plan to combine methods from time-to-event analysis and network modeling into an approach that capitalizes on the inherently complex dependency structures in such data.
- AG Brandes (Algorithmik)
|Industrie||838/11||01.01.2012 – 31.12.2012|
|Period:||01.01.2012 – 31.12.2012|