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: