Formal Analysis on Interaction Flow and Information Cocoon Based on Probabilistic Graph

The recommendation algorithm may feed to end users information by analyzing the potential interests of the users in last interaction period, and finally the information obtained by the users may be constrained within a limited range. This problem is so-called information cocoon and has be attracted more and more attentions. In this paper, we study this problem in the perspective from both service providers and end users. An analysis model in terms of probabilistic transfer graph is proposed, and corresponding matrix is analyzed. We also propose a method to compute the power of matrix by approximating any transfer graph into a symmetric matrix, and the stability on the probability can be easily computed by matrix division and eigenvalues.