We consider the problem of estimating the location of a single change point in a network
generated by a dynamic stochastic block model mechanism. This model produces …

Change point detection aims to find the locations of sudden changes in the network
structure, which persist with time. However, most current methods usually focus on how to …

Recently, there has been a lot of interest in monitoring and identifying changes in dynamic
networks, which has led to the development of a variety of monitoring methods. New …

We develop a real-time anomaly detection method for directed activity on large, sparse
networks. We model the propensity for future activity using a dynamic logistic model with …

Structural changes occur in dynamic networks quite frequently and its detection is an
important question in many situations such as fraud detection or cybersecurity. Real-life …

Detecting or recognizing event related change points in dynamic networks becomes an
increasingly important task, as a change in network's structure may associate with a change …

Many complex networked systems, both natural and human-made, exhibit periodic behavior
driven by underlying seasonal processes: election cycles and regular sporting events in …

Prediction of events is imperative in many areas of social network (SN) applications. These
events influence the temporal evolutionary characteristic of social networks. A study of these …

The ubiquity of relational data has motivated an extensive literature on network analysis,
and over the last two decades the latent space approach has become a popular network …

Detecting event related change points on dynamic networks becomes an increasingly
important task, as a change in network's structure may associate with a change in function of …