Many real-world relations can be represented by signed networks with positive and negative
links, as a result of which signed network analysis has attracted increasing attention from …

Recent development in the area of social networks has sought attention of the researchers
to crunch and analyse the data and information of the users to retrieve relevant knowledge …

Due to the fact much of today's data can be represented as graphs, there has been a
demand for generalizing neural network models for graph data. One recent direction that …

In social networks, link prediction predicts missing links in current networks and new or
dissolution links in future networks, is important for mining and analyzing the evolution of …

Social networks have become very important for networking, communications, and content
sharing. Social networking applications generate a huge amount of data on a daily basis …

Influence diffusion and influence maximization in large-scale online social networks (OSNs)
have been extensively studied because of their impacts on enabling effective online viral …

The increasing popularity of social media encourages more and more users to participate in
various online activities and produces data in an unprecedented rate. Social media data is …

We consider signed networks in which connections or edges can be either positive
(friendship, trust, alliance) or negative (dislike, distrust, conflict). Early literature in graph …

Node classification in social networks has been proven to be useful in many real-world
applications. The vast majority of existing algorithms focus on unsigned social networks (or …

Signed network analysis has attracted increasing attention in recent years. This is in part
because research on signed network analysis suggests that negative links have added …