Team members
Nitin Agarwal
Yandong Liu
Yanbo Xu
Ming Sun
LDA results
ATM results
Gibbs Sampling for Collaboration Influence Model
We want , the posterior distribution of topic Z, (author, collaborator) pair X and which favor of collaboration over influence R given the words W in the corpus:
We begin by calculating and :
,
where P is the number of all the different author-collaborator-favor of collaboration combination (a,a',r).
So the Gibbs sampling of :
Further manipulation can turn the above equation into update equations for the topic and author-collaboration of each corpus token: