PROJECT TITLE :

Triadic Closure Pattern Analysis and Prediction in Social Networks

ABSTRACT:

We tend to study the matter of group formation in on-line social networks. In particular, we concentrate on one in every of the most important human groups—the triad—and attempt to understand how closed triads are fashioned in dynamic networks, by employing information from a giant microblogging network as the idea of our study. We have a tendency to formally outline the problem of triadic closure prediction and conduct a systematic investigation. The study reveals how user demographics, network characteristics, and social properties influence the formation of triadic closure. We have a tendency to additionally gift a probabilistic graphical model to predict whether 3 persons will type a closed triad in a very dynamic network. Different kernel functions are incorporated into the proposed graphical model to quantify the similarity between triads. Our experimental results with the massive microblogging dataset demonstrate the effectiveness (+ten percent over alternative ways in terms of F1-Score) of the proposed model for the prediction of triadic closure formation.