Archit Tiwari & Mohammed Bakhtawar Ahmed (Assistant Professor) Amity University Chhattisgarh
Abstract
A social network is usually conceived as
a graph in which individuals in the network are
represented by the nodes and the nodes are
connected to each other by links which depict the
relations among the individuals. The term
“community” for any group of nodes that are
densely connected among themselves and sparsely
connected to others. As time evolves, communities
in a social network may undergo various changes
(split, expand, shrink, stable, merge) known as
critical events. Prediction of critical events is an
important and difficult issue in the study of social
networks. This paper proposes a sliding window
analysis, an autoregressive model and survival
analysis techniques. The autoregressive model is
here to simulate the evolution of the community
structure, and the survival analysis techniques allow
the prediction of future changes the community may
undergo. In our approach Critical events are treated
based on a weighting scheme.